Soliciting data indicating at least one subjective user state in response to acquisition of data indicating at least one objective occurrence

ABSTRACT

Systems and articles of manufacture for implementing a method that includes, but is not limited to: acquiring objective occurrence data including data indicating occurrence of at least one objective occurrence; soliciting, in response to the acquisition of the objective occurrence data, subjective user state data including data indicating occurrence of at least one subjective user state associated with a user; acquiring the subjective user state data and correlating the subjective user state data with the objective occurrence data. In some implementations, the soliciting of the subjective user state data may involve soliciting the data from the user by requesting a selection of a subjective user state from a plurality of indicated alternative subjective user states. In the same or different implementations, the correlating of the subjective user state data with the objective occurrence data may involve determining at least one sequential pattern associated with occurrence of the at least one subjective user state and occurrence of the at least one objective occurrence. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is related to and claims the benefit of theearliest available effective filing date(s) from the following listedapplication(s) (the “Related Applications”) (e.g., claims earliestavailable priority dates for other than provisional patent applicationsor claims benefits under 35 USC §119(e) for provisional patentapplications, for any and all parent, grandparent, great-grandparent,etc. applications of the Related Application(s)). All subject matter ofthe Related Applications and of any and all parent, grandparent,great-grandparent, etc. applications of the Related Applications isincorporated herein by reference to the extent such subject matter isnot inconsistent herewith.

Related Applications

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/313,659, entitled CORRELATING SUBJECTIVE USERSTATES WITH OBJECTIVE OCCURRENCES ASSOCIATED WITH A USER, naming ShawnP. Firminger, Jason Garms, Edward K. Y. Jung, Chris D. Karkanias, EricC. Leuthardt, Royce A. Levien, Robert W. Lord, Mark A. Malamud, John D.Rinaldo, Jr., Clarence T. Tegreene, Kristin M. Tolle, and Lowell L.Wood, Jr., as inventors, filed 21 Nov. 2008now U.S. Pat. No. 8,046,455,which is currently, or is an application of which a currently co-pendingapplication is entitled to the benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/315,083, entitled CORRELATING SUBJECTIVE USERSTATES WITH OBJECTIVE OCCURRENCES ASSOCIATED WITH A USER, naming ShawnP. Firminger, Jason Garms, Edward K. Y. Jung, Chris D. Karkanias, EricC. Leuthardt, Royce A. Levien, Robert W. Lord, Mark A. Malamud, John D.Rinaldo, Jr., Clarence T. Tegreene, Kristin M. Tolle, and Lowell L.Wood, Jr., as inventors, filed 26 Nov. 2008, which is currentlyco-pending, or is an application of which a currently co-pendingapplication is entitled to the benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/319,135, entitled CORRELATING DATA INDICATING ATLEAST ONE SUBJECTIVE USER STATE WITH DATA INDICATING AT LEAST ONEOBJECTIVE OCCURRENCE ASSOCIATED WITH A USER, naming Shawn P. Firminger;Jason Garms; Edward K. Y. Jung; Chris D. Karkanias; Eric C. Leuthardt;Royce A. Levien; Robert W. Lord; Mark A. Malamud; John D. Rinaldo, Jr.;Clarence T. Tegreene; Kristin M. Tolle; Lowell L. Wood, Jr. asinventors, filed 31 Dec. 2008, which is currently co-pending, or is anapplication of which a currently co-pending application is entitled tothe benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/319,134, entitled CORRELATING DATA INDICATING ATLEAST ONE SUBJECTIVE USER STATE WITH DATA INDICATING AT LEAST ONEOBJECTIVE OCCURRENCE ASSOCIATED WITH A USER, naming Shawn P. Firminger;Jason Garms; Edward K. Y. Jung; Chris D. Karkanias; Eric C. Leuthardt;Royce A. Levien; Robert W. Lord; Mark A. Malamud; John D. Rinaldo, Jr.;Clarence T. Tegreene; Kristin M. Tolle; Lowell L. Wood, Jr. asinventors, filed 31 Dec. 2008, which is currently co-pending, or is anapplication of which a currently co-pending application is entitled tothe benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/378,162, entitled SOLICITING DATA INDICATING ATLEAST ONE OBJECTIVE OCCURRENCE IN RESPONSE TO ACQUISITION OF DATAINDICATING AT LEAST ONE SUBJECTIVE USER STATE, naming Shawn P.Firminger; Jason Garms; Edward K.Y. Jung; Chris D. Karkanias; Eric C.Leuthardt; Royce A. Levien; Robert W. Lord; Mark A. Malamud; John D.Rinaldo, Jr.; Clarence T. Tegreene; Kristin M. Tolle; Lowell L. Wood,Jr. as inventors, filed 9 Feb. 2009 now U.S. Pat. No. 8,028,063, whichis currently, an application currently entitled to the benefit of thefiling date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/378,288, entitled SOLICITING DATA INDICATING ATLEAST ONE OBJECTIVE OCCURRENCE IN RESPONSE TO ACQUISITION OF DATAINDICATING AT LEAST ONE SUBJECTIVE USER STATE, naming Shawn P.Firminger; Jason Garms; Edward K.Y. Jung; Chris D. Karkanias; Eric C.Leuthardt; Royce A. Levien; Robert W. Lord; Mark A. Malamud; John D.Rinaldo, Jr.; Clarence T. Tegreene; Kristin M. Tolle; Lowell L. Wood,Jr. as inventors, filed 11 Feb. 2009now U.S. Pat. No. 8,032,628, whichis currently, an application currently entitled to the benefit of thefiling date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/380,409, entitled SOLICITING DATA INDICATING ATLEAST ONE SUBJECTIVE USER STATE IN RESPONSE TO ACQUISITION OF DATAINDICATING AT LEAST ONE OBJECTIVE OCCURRENCE, naming Shawn P. Firminger;Jason Garms; Edward K.Y. Jung; Chris D. Karkanias; Eric C. Leuthardt;Royce A. Levien; Robert W. Lord; Mark A. Malamud; John D. Rinaldo, Jr.;Clarence T. Tegreene; Kristin M. Tolle; Lowell L. Wood, Jr. asinventors, filed 25 Feb. 2009 now U.S. Pat. 8,010,661, which iscurrently, an application currently entitled to the benefit of thefiling date.

The United States Patent Office (USPTO) has published a notice to theeffect that the USPTO's computer programs require that patent applicantsreference both a serial number and indicate whether an application is acontinuation or continuation-in-part. Stephen G. Kunin, Benefit ofPrior-Filed Application, USPTO Official Gazette Mar. 18, 2003, availableat http://www.uspto.gov/web/offices/com/sol/og/2003/week11/patbene.htm.The present Applicant Entity (hereinafter “Applicant”) has providedabove a specific reference to the application(s)from which priority isbeing claimed as recited by statute. Applicant understands that thestatute is unambiguous in its specific reference language and does notrequire either a serial number or any characterization, such as“continuation” or “continuation-in-part,” for claiming priority to U.S.patent applications. Notwithstanding the foregoing, Applicantunderstands that the USPTO's computer programs have certain data entryrequirements, and hence Applicant is designating the present applicationas a continuation-in-part of its parent applications as set forth above,but expressly points out that such designations are not to be construedin any way as any type of commentary and/or admission as to whether ornot the present application contains any new matter in addition to thematter of its parent application(s).

All subject matter of the Related Applications and of any and allparent, grandparent, great-grandparent, etc. applications of the RelatedApplications is incorporated herein by reference to the extent suchsubject matter is not inconsistent herewith.

SUMMARY

A computationally implemented method includes, but is not limited to:acquiring objective occurrence data including data indicating occurrenceof at least one objective occurrence; soliciting, in response to theacquisition of the objective occurrence data, subjective user state dataincluding data indicating occurrence of at least one subjective userstate associated with a user; acquiring the subjective user state data;and correlating the subjective user state data with the objectiveoccurrence data. In addition to the foregoing, other method aspects aredescribed in the claims, drawings, and text forming a part of thepresent disclosure.

In one or more various aspects, related systems include but are notlimited to circuitry and/or programming for effecting theherein-referenced method aspects; the circuitry and/or programming canbe virtually any combination of hardware, software, and/or firmwareconfigured to effect the herein-referenced method aspects depending uponthe design choices of the system designer.

A system in the form of a machine, article of manufacture, orcomposition of matter that includes, but is not limited to: an objectiveoccurrence data acquisition module configured to acquire objectiveoccurrence data, the objective occurrence data to be acquired includingdata indicating occurrence of at least one objective occurrence; asubjective user state data solicitation module configured to solicitsubjective user state data including data indicating occurrence of atleast one subjective user state associated with a user in response tothe acquisition of the objective occurrence data, wherein the subjectiveuser state data solicitation module includes a subjective user statedata solicitation module configured to solicit the data indicatingoccurrence of at least one subjective user state associated with a userfrom the user, wherein the subjective user state data solicitationmodule includes a requesting module configured to request for aselection of a subjective user state from a plurality of indicatedalternative subjective user states; a subjective user state dataacquisition module configured to acquire the subjective user state data;and a correlation module configured to correlate the objectiveoccurrence data with the subjective user state data. In addition to theforegoing, other system aspects are described in the claims, drawings,and text forming a part of the present disclosure.

A system in the form of a machine, article of manufacture, orcomposition of matter that includes, but is not limited to: an objectiveoccurrence data acquisition module configured to acquire objectiveoccurrence data, the objective occurrence data to be acquired includingdata indicating occurrence of at least one objective occurrence; asubjective user state data solicitation module configured to solicitsubjective user state data including data indicating occurrence of atleast one subjective user state associated with a user in response tothe acquisition of the objective occurrence data; a subjective userstate data acquisition module configured to acquire the subjective userstate data; and a correlation module configured to correlate theobjective occurrence data with the subjective user state data, whereinsaid correlation module includes a sequential pattern determinationmodule configured to determine at least one sequential patternassociated with occurrence of the at least one subjective user state andoccurrence of the at least one objective occurrence. In addition to theforegoing, other system aspects are described in the claims, drawings,and text forming a part of the present disclosure.

An article of manufacture including a non-transitory storage mediumbearing one or more instructions for acquiring objective occurrencedata, the objective occurrence data to be acquired including dataindicating occurrence of at least one objective occurrence; one or moreinstructions for soliciting subjective user state data including dataindicating occurrence of at least one subjective user state associatedwith a user in response to the acquisition of the objective occurrencedata; one or more instructions for acquiring the subjective user statedata; and one or more instructions for correlating the objectiveoccurrence data with the subjective user state data, wherein said one ormore instructions for correlating the objective occurrence data with thesubjective user state data includes one or more instructions fordetermining at least one sequential pattern associated with occurrenceof the at least one subjective user state and occurrence of the at leastone objective occurrence. In addition to the foregoing, other computerprogram product aspects are described in the claims, drawings, and textforming a part of the present disclosure.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featureswill become apparent by reference to the drawings and the followingdetailed description.

BRIEF DESCRIPTION OF THE FIGURES

FIGS. 1 a and 1 b show a high-level block diagram of a computing device10 operating in a network environment.

FIG. 2 a shows another perspective of the objective occurrence dataacquisition module 102 of the computing device 10 of FIG. 1 b.

FIG. 2 b shows another perspective of the subjective user state datasolicitation module 103 of the computing device 10 of FIG. 1 b.

FIG. 2 c shows another perspective of the subjective user state dataacquisition module 104 of the computing device 10 of FIG. 1 b.

FIG. 2 d shows another perspective of the correlation module 106 of thecomputing device 10 of FIG. 1 b.

FIG. 2 e shows another perspective of the presentation module 108 of thecomputing device 10 of FIG. 1 b.

FIG. 2 f shows another perspective of the one or more applications 126of the computing device 10 of FIG. 1 b.

FIG. 3 is a high-level logic flowchart of a process.

FIG. 4 a is a high-level logic flowchart of a process depictingalternate implementations of the objective occurrence data acquisitionoperation 302 of FIG. 3.

FIG. 4 b is a high-level logic flowchart of a process depictingalternate implementations of the objective occurrence data acquisitionoperation 302 of FIG. 3.

FIG. 4 c is a high-level logic flowchart of a process depictingalternate implementations of the objective occurrence data acquisitionoperation 302 of FIG. 3.

FIG. 5 a is a high-level logic flowchart of a process depictingalternate implementations of the subjective user state data solicitationoperation 304 of FIG. 3.

FIG. 5 b is a high-level logic flowchart of a process depictingalternate implementations of the subjective user state data solicitationoperation 304 of FIG. 3.

FIG. 5 c is a high-level logic flowchart of a process depictingalternate implementations of the subjective user state data solicitationoperation 304 of FIG. 3.

FIG. 5 d is a high-level logic flowchart of a process depictingalternate implementations of the subjective user state data solicitationoperation 304 of FIG. 3.

FIG. 6 a is a high-level logic flowchart of a process depictingalternate implementations of the subjective user state data acquisitionoperation 306 of FIG. 3.

FIG. 6 b is a high-level logic flowchart of a process depictingalternate implementations of the subjective user state data acquisitionoperation 306 of FIG. 3.

FIG. 6 c is a high-level logic flowchart of a process depictingalternate implementations of the subjective user state data acquisitionoperation 306 of FIG. 3.

FIG. 7 a is a high-level logic flowchart of a process depictingalternate implementations of the correlation operation 308 of FIG. 3.

FIG. 7 b is a high-level logic flowchart of a process depictingalternate implementations of the correlation operation 308 of FIG. 3.

FIG. 8 is a high-level logic flowchart of another process.

FIG. 9 is a high-level logic flowchart of a process depicting alternateimplementations of the presentation operation 810 of FIG. 8.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented here.

A recent trend that is becoming increasingly popular in thecomputing/communication field is to electronically record one'sfeelings, thoughts, and other aspects of the person's everyday life ontoan open diary. One place where such open diaries are maintained are atsocial networking sites commonly known as “blogs” where one or moreusers may report or post their thoughts and opinions on various topics,latest news, current events, and various other aspects of the users'everyday life. The process of reporting or posting blog entries iscommonly referred to as blogging. Other social networking sites mayallow users to update their personal information via, for example,social network status reports in which a user may report or post forothers to view the latest status or other aspects of the user.

A more recent development in social networking is the introduction andexplosive growth of microblogs in which individuals or users (referredto as “microbloggers”) maintain open diaries at microblog websites(e.g., otherwise known as “twitters”) by continuously orsemi-continuously posting microblog entries. A microblog entry (e.g.,“tweet”) is typically a short text message that is usually not more than140 characters long. The microblog entries posted by a microblogger mayreport on any aspect of the microblogger's daily life.

The various things that are typically posted through microblog entriesmay be categorized into one of at least two possible categories. Thefirst category of things that may be reported through microblog entriesare “objective occurrences” associated with the microblogger. Objectiveoccurrences that are associated with a microblogger may be anycharacteristic, event, happening, or any other aspects associated withor are of interest to the microblogger that can be objectively reportedby the microblogger, a third party, or by a device. These things wouldinclude, for example, food, medicine, or nutraceutical intake of themicroblogger, certain physical characteristics of the microblogger suchas blood sugar level or blood pressure that can be objectively measured,daily activities of the microblogger observable by others or by adevice, external events that may not be directly related to the usersuch as the local weather or the performance of the stock market (whichthe microblogger may have an interest in), activities of others (e.g.,spouse or boss) that may directly or indirectly affect the microblogger,and so forth.

A second category of things that may be reported or posted throughmicroblogging entries include “subjective user states” of themicroblogger. Subjective user states of a microblogger include anysubjective state or status associated with the microblogger that canonly be typically reported by the microblogger (e.g., generally cannotbe reported by a third party or by a device). Such states including, forexample, the subjective mental state of the microblogger (e.g., “I amfeeling happy”), the subjective physical states of the microblogger(e.g., “my ankle is sore” or “my ankle does not hurt anymore” or “myvision is blurry”), and the subjective overall state of the microblogger(e.g., “I'm good” or “I'm well”). Note that the term “subjective overallstate” as will be used herein refers to those subjective states that maynot fit neatly into the other two categories of subjective user statesdescribed above (e.g., subjective mental states and subjective physicalstates). Although microblogs are being used to provide a wealth ofpersonal information, they have thus far been primarily limited to theiruse as a means for providing commentaries and for maintaining opendiaries.

In accordance with various embodiments, methods, systems, and computerprogram products are provided for, among other things, soliciting andacquiring subjective user state data including data indicative of atleast one subjective user state associated with a user in response toacquisition of objective occurrence data including data indicating atleast one objective occurrence. As will be further described herein, insome embodiments, the solicitation of the subjective user state datamay, in addition to being prompted by the acquisition of the objectiveoccurrence data, may be prompted based on historical data. Suchhistorical data may be historical data that is associated with the user,associated with a group of users, associated with a segment of thegeneral population, or associated with the general population.

The methods, systems, and computer program products may then correlatethe subjective user state data (e.g., data that indicate one or moresubjective user states of a user) with the objective occurrence data(e.g., data that indicate one or more objective occurrences associatedwith the user). By correlating the subjective user state data with theobjective occurrence data, a causal relationship between one or moreobjective occurrences (e.g., cause) and one or more subjective userstates (e.g., result) associated with a user (e.g., a blogger ormicroblogger) may be determined in various alternative embodiments. Forexample, determining that the last time a user ate a banana (e.g.,objective occurrence), the user felt “good” (e.g., subjective userstate) or determining whenever a user eats a banana the user always orsometimes feels good. Note that an objective occurrence does not need tooccur prior to a corresponding subjective user state but instead, mayoccur subsequent or concurrently with the incidence of the subjectiveuser state. For example, a person may become “gloomy” (e.g., subjectiveuser state) whenever it is about to rain (e.g., objective occurrence) ora person may become gloomy while (e.g., concurrently) it is raining.

In various embodiments, subjective user state data may include data thatindicate the occurrence of one or more subjective user states associatedwith a user. As briefly described above, a “subjective user state” is inreference to any state or status associated with a user (e.g., a bloggeror microblogger) at any moment or interval in time that only the usercan typically indicate or describe. Such states include, for example,the subjective mental state of the user (e.g., user is feeling sad), thesubjective physical state (e.g., physical characteristic) of the userthat only the user can typically indicate (e.g., a backache or an easingof a backache as opposed to blood pressure which can be reported by ablood pressure device and/or a third party), and the subjective overallstate of the user (e.g., user is “good”).

Examples of subjective mental states include, for example, happiness,sadness, depression, anger, frustration, elation, fear, alertness,sleepiness, and so forth. Examples of subjective physical statesinclude, for example, the presence, easing, or absence of pain, blurryvision, hearing loss, upset stomach, physical exhaustion, and so forth.Subjective overall states may include any subjective user states thatcannot be easily categorized as a subjective mental state or as asubjective physical state. Examples of overall states of a user that maybe subjective user states include, for example, the user being good,bad, exhausted, lack of rest, wellness, and so forth.

In contrast, “objective occurrence data,” which may also be referred toas “objective context data,” may include data that indicate one or moreobjective occurrences associated with the user that occurred atparticular intervals or points in time. In some embodiments, anobjective occurrence may be any physical characteristic, event,happenings, or any other aspect that may be associated with, is ofinterest to, or may somehow impact a user that can be objectivelyreported by at least a third party or a sensor device. Note, however,that such objective occurrence data does not have to be actuallyprovided by a sensor device or by a third party, but instead, may bereported by the user himself or herself (e.g., via microblog entries).Examples of objectively reported occurrences that could be indicated bythe objective occurrence data include, for example, a user's food,medicine, or nutraceutical intake, the user's location at any givenpoint in time, a user's exercise routine, a user's physiologicalcharacteristics such as blood pressure, social or professionalactivities, the weather at a user's location, activities associated withthird parties, occurrence of external events such as the performance ofthe stock market, and so forth.

The term “correlating” as will be used herein may be in reference to adetermination of one or more relationships between at least twovariables. Alternatively, the term “correlating” may merely be inreference to the linking or associating of at least two variables. Inthe following exemplary embodiments, the first variable is subjectiveuser state data that represents at least one subjective user state of auser and the second variable is objective occurrence data thatrepresents at least one objective occurrence. In embodiments where thesubjective user state data includes data that indicates multiplesubjective user states, each of the subjective user states representedby the subjective user state data may be the same or similar type ofsubjective user state (e.g., user being happy) at different intervals orpoints in time. Alternatively, different types of subjective user state(e.g., user being happy and user being sad) may be represented by thesubjective user state data. Similarly, in embodiments where multipleobjective occurrences are indicated by the objective occurrence data,each of the objective occurrences may represent the same or similar typeof objective occurrence (e.g., user exercising) at different intervalsor points in time, or alternatively, different types of objectiveoccurrence (e.g., user exercising and user resting).

Various techniques may be employed for correlating subjective user statedata with objective occurrence data in various alternative embodiments.For example, in some embodiments, correlating the objective occurrencedata with the subjective user state data may be accomplished bydetermining a sequential pattern associated with at least one subjectiveuser state indicated by the subjective user state data and at least oneobjective occurrence indicated by the objective occurrence data. Inother embodiments, correlating of the objective occurrence data with thesubjective user state data may involve determining multiple sequentialpatterns associated with multiple subjective user states and multipleobjective occurrences.

A sequential pattern, as will be described herein, may define timeand/or temporal relationships between two or more events (e.g., one ormore subjective user states and one or more objective occurrences). Inorder to determine a sequential pattern, subjective user state dataincluding data indicating occurrence of at least one subjective userstate associated with a user may be solicited in response to anacquisition of objective occurrence data including data indicatingoccurrence of at least one objective occurrence.

For example, if a user (or a third party source such as a contentprovider or another user) reports that the weather on a particular day(e.g., objective occurrence) was bad (e.g., cloudy weather) then asolicitation for subjective user state data including data indicatingoccurrence of at least one subjective user state associated with theuser on that particular day may be made. Such solicitation of subjectiveuser state data may be prompted based, at least in part, on thereporting of the objective occurrence (e.g., cloudy weather) and basedon historical data such as historical data that indicates or suggeststhat the user tends to get gloomy when the weather is bad (e.g., cloudy)or based on historical data that indicates that people in the generalpopulation tend to get gloomy whenever the weather is bad. In someembodiments, such historical data may indicate or define one or morehistorical sequential patterns of the user or of the general populationas they relate to subjective user states and objective occurrences.

As briefly described above, a sequential pattern may merely indicate orrepresent the temporal relationship or relationships between at leastone subjective user state and at least one objective occurrence (e.g.,whether the incidence or occurrence of the at least one subjective userstate occurred before, after, or at least partially concurrently withthe incidence of the at least one objective occurrence). In alternativeimplementations, and as will be further described herein, a sequentialpattern may indicate a more specific time relationship between theincidences of one or more subjective user states and the incidences ofone or more objective occurrences. For example, a sequential pattern mayrepresent the specific pattern of events (e.g., one or more objectiveoccurrences and one or more subjective user states) that occurs along atimeline.

The following illustrative example is provided to describe how asequential pattern associated with at least one subjective user stateand at least one objective occurrence may be determined based, at leastin part, on the temporal relationship between the incidence of the atleast one subjective user state and the incidence of the at least oneobjective occurrence in accordance with some embodiments. For theseembodiments, the determination of a sequential pattern may initiallyinvolve determining whether the incidence of the at least one subjectiveuser state occurred within some predefined time increments of theincidence of the one objective occurrence. That is, it may be possibleto infer that those subjective user states that did not occur within acertain time period from the incidence of an objective occurrence arenot related or are unlikely related to the incidence of that objectiveoccurrence.

For example, suppose a user during the course of a day eats a banana andalso has a stomach ache sometime during the course of the day. If theconsumption of the banana occurred in the early morning hours but thestomach ache did not occur until late that night, then the stomach achemay be unrelated to the consumption of the banana and may bedisregarded. On the other hand, if the stomach ache had occurred withinsome predefined time increment, such as within 2 hours of consumption ofthe banana, then it may be concluded that there is a correlation or linkbetween the stomach ache and the consumption of the banana. If so, atemporal relationship between the consumption of the banana and theoccurrence of the stomach ache may be determined. Such a temporalrelationship may be represented by a sequential pattern. Such asequential pattern may simply indicate that the stomach ache (e.g., asubjective user state) occurred after (rather than before orconcurrently) the consumption of banana (e.g., an objective occurrence).

Other factors may also be referenced and examined in order to determinea sequential pattern and whether there is a relationship (e.g., causalrelationship) between an objective occurrence and a subjective userstate. These factors may include, for example, historical data (e.g.,historical medical data such as genetic data or past history of the useror historical data related to the general population regarding, forexample, stomach aches and bananas) as briefly described above.Alternatively, a sequential pattern may be determined for multiplesubjective user states and multiple objective occurrences. Such asequential pattern may particularly map the exact temporal or timesequencing of the various events (e.g., subjective user states and/orobjective occurrences). The determined sequential pattern may then beused to provide useful information to the user and/or third parties.

The following is another illustrative example of how subjective userstate data may be correlated with objective occurrence data bydetermining multiple sequential patterns and comparing the sequentialpatterns with each other. Suppose, for example, a user such as amicroblogger reports that the user ate a banana on a Monday. Theconsumption of the banana, in this example, is a reported firstobjective occurrence associated with the user. The user then reportsthat 15 minutes after eating the banana, the user felt very happy. Thereporting of the emotional state (e.g., felt very happy) is, in thisexample, a reported first subjective user state. Thus, the reportedincidence of the first objective occurrence (e.g., eating the banana)and the reported incidence of the first subjective user state (user feltvery happy) on Monday may be represented by a first sequential pattern.

On Tuesday, the user reports that the user ate another banana (e.g., asecond objective occurrence associated with the user). The user thenreports that 20 minutes after eating the second banana, the user feltsomewhat happy (e.g., a second subjective user state). Thus, thereported incidence of the second objective occurrence (e.g., eating thesecond banana) and the reported incidence of the second subjective userstate (user felt somewhat happy) on Tuesday may be represented by asecond sequential pattern. Note that in this example, the occurrences ofthe first subjective user state and the second subjective user state maybe indicated by subjective user state data while the occurrences of thefirst objective occurrence and the second objective occurrence may beindicated by objective occurrence data.

In a slight variation of the above example, suppose the user hadforgotten to report for Tuesday the feeling of being somewhat happy butdoes report consuming the second banana on Tuesday. This may result inthe user being asked, based on the reporting of the user consuming thebanana on Tuesday, as to how the user felt on Tuesday or how the userfelt after eating the banana on Tuesday. Asking such questions may beprompted both in response to the reporting of the consumption of thesecond banana on Tuesday (e.g., an objective occurrence) and onreferencing historical data (e.g., first sequential pattern derived fromMonday's consumption of banana and feeling happy). Upon the userindicating feeling somewhat happy on Tuesday, a second sequentialpattern may be determined.

In any event, by comparing the first sequential pattern with the secondsequential pattern, the subjective user state data may be correlatedwith the objective occurrence data. In some implementations, thecomparison of the first sequential pattern with the second sequentialpattern may involve trying to match the first sequential pattern withthe second sequential pattern by examining certain attributes and/ormetrics. For example, comparing the first subjective user state (e.g.,user felt very happy) of the first sequential pattern with the secondsubjective user state (e.g., user felt somewhat happy) of the secondsequential pattern to see if they at least substantially match or arecontrasting (e.g., being very happy in contrast to being slightly happyor being happy in contrast to being sad). Similarly, comparing the firstobjective occurrence (e.g., eating a banana) of the first sequentialpattern may be compared to the second objective occurrence (e.g., eatingof another banana) of the second sequential pattern to determine whetherthey at least substantially match or are contrasting.

A comparison may also be made to determine if the extent of timedifference (e.g., 15 minutes) between the first subjective user state(e.g., user being very happy) and the first objective occurrence (e.g.,user eating a banana) matches or are at least similar to the extent oftime difference (e.g., 20 minutes) between the second subjective userstate (e.g., user being somewhat happy) and the second objectiveoccurrence (e.g., user eating another banana). These comparisons may bemade in order to determine whether the first sequential pattern matchesthe second sequential pattern. A match or substantial match wouldsuggest, for example, that a subjective user state (e.g., happiness) islinked to a particular objective occurrence (e.g., consumption ofbanana).

As briefly described above, the comparison of the first sequentialpattern with the second sequential pattern may include a determinationas to whether, for example, the respective subjective user states andthe respective objective occurrences of the sequential patterns arecontrasting subjective user states and/or contrasting objectiveoccurrences. For example, suppose in the above example the user hadreported that the user had eaten a whole banana on Monday and felt veryenergetic (e.g., first subjective user state) after eating the wholebanana (e.g., first objective occurrence). Suppose that the user alsoreported that on Tuesday he ate a half a banana instead of a wholebanana and only felt slightly energetic (e.g., second subjective userstate) after eating the half banana (e.g., second objective occurrence).In this scenario, the first sequential pattern (e.g., feeling veryenergetic after eating a whole banana) may be compared to the secondsequential pattern (e.g., feeling slightly energetic after eating only ahalf of a banana) to at least determine whether the first subjectiveuser state (e.g., being very energetic) and the second subjective userstate (e.g., being slightly energetic) are contrasting subjective userstates. Another determination may also be made during the comparison todetermine whether the first objective occurrence (eating a whole banana)is in contrast with the second objective occurrence (e.g., eating a halfof a banana).

In doing so, an inference may be made that eating a whole banana insteadof eating only a half of a banana makes the user happier or eating morebanana makes the user happier. Thus, the word “contrasting” as used herewith respect to subjective user states refers to subjective user statesthat are the same type of subjective user states (e.g., the subjectiveuser states being variations of a particular type of subjective userstates such as variations of subjective mental states). Thus, forexample, the first subjective user state and the second subjective userstate in the previous illustrative example are merely variations ofsubjective mental states (e.g., happiness). Similarly, the use of theword “contrasting” as used here with respect to objective occurrencesrefers to objective states that are the same type of objectiveoccurrences (e.g., consumption of food such as banana).

As those skilled in the art will recognize, a stronger correlationbetween the subjective user state data and the objective occurrence datacould be obtained if a greater number of sequential patterns (e.g., ifthere was a third sequential pattern, a fourth sequential pattern, andso forth, that indicated that the user became happy or happier wheneverthe user ate bananas) are used as a basis for the correlation. Note thatfor ease of explanation and illustration, each of the exemplarysequential patterns to be described herein will be depicted as asequential pattern of an occurrence of a single subjective user stateand an occurrence of a single objective occurrence. However, thoseskilled in the art will recognize that a sequential pattern, as will bedescribed herein, may also be associated with occurrences of multipleobjective occurrences and/or multiple subjective user states. Forexample, suppose the user had reported that after eating a banana, hehad gulped down a can of soda. The user then reported that he becamehappy but had an upset stomach. In this example, the sequential patternassociated with this scenario will be associated with two objectiveoccurrences (e.g., eating a banana and drinking a can of soda) and twosubjective user states (e.g., user having an upset stomach and feelinghappy).

In some embodiments, and as briefly described earlier, the sequentialpatterns derived from subjective user state data and objectiveoccurrence data may be based on temporal relationships between objectiveoccurrences and subjective user states. For example, whether asubjective user state occurred before, after, or at least partiallyconcurrently with an objective occurrence. For instance, a plurality ofsequential patterns derived from subjective user state data andobjective occurrence data may indicate that a user always has a stomachache (e.g., subjective user state) after eating a banana (e.g., firstobjective occurrence).

FIGS. 1 a and 1 b illustrate an example environment in accordance withvarious embodiments. In the illustrated environment, an exemplary system100 may include at least a computing device 10 (see FIG. 1 b) that maybe employed in order to, among other things, acquire objectiveoccurrence data 70* including data indicating occurrence of at least oneobjective occurrence, solicit and acquire subjective user state data 60including data indicating occurrence of at least one subjective userstate 60 a associated with a user 20* in response to the acquisition ofthe objective occurrence data 70*, and to correlate the subjective userstate data 60 with the objective occurrence data 70*. Note that in thefollowing, “*” indicates a wildcard. Thus, user 20* may indicate a user20 a or a user 20 b of FIGS. 1 a and 1 b.

In some embodiments, the computing device 10 may be a network server inwhich case the computing device 10 may communicate with a user 20 a viaa mobile device 30 and through a wireless and/or wired network 40. Anetwork server, as will be described herein, may be in reference to aserver located at a single network site or located across multiplenetwork sites or a conglomeration of servers located at multiple networksites. The mobile device 30 may be a variety of computing/communicationdevices including, for example, a cellular phone, a personal digitalassistant (PDA), a laptop, a desktop, or other types ofcomputing/communication device that can communicate with the computingdevice 10.

In alternative embodiments, the computing device 10 may be a localcomputing device that communicates directly with a user 20 b. For theseembodiments, the computing device 10 may be any type of handheld devicesuch as a cellular telephone, a PDA, or other types ofcomputing/communication devices such as a laptop computer, a desktopcomputer, and so forth. In various embodiments, the computing device 10may be a peer-to-peer network component device. In some embodiments, thecomputing device 10 may operate via a web 2.0 construct.

In embodiments where the computing device 10 is a server, the computingdevice 10 may obtain the subjective user state data 60 indirectly from auser 20 a via a network interface 120. In alternative embodiments inwhich the computing device 10 is a local device such as a handhelddevice (e.g., cellular telephone, personal digital assistant, etc.), thesubjective user state data 60 may be directly obtained from a user 20 bvia a user interface 122. As will be further described, the computingdevice 10 may acquire the objective occurrence data 70* from one or morealternative sources.

For ease of illustration and explanation, the following systems andoperations to be described herein will be generally described in thecontext of the computing device 10 being a network server. However,those skilled in the art will recognize that these systems andoperations may also be implemented when the computing device 10 is alocal device such as a handheld device that may communicate directlywith a user 20 b.

Assuming that the computing device 10 is a server, the computing device10, in various implementations, may be configured to acquire objectiveoccurrence data 70* including data indicating incidence or occurrence ofat least one objective occurrence via a network interface 120 or via auser interface 122. In some implementations, the objective occurrencedata 70* may further include additional data that may indicateoccurrences of one or more additional objective occurrences (e.g., dataindicating occurrence of at least a second objective occurrence). Theobjective occurrence data 70* may be provided by a user 20*, by one ormore third parties 50 (e.g., third party sources), or by one or moresensors 35.

For example, in some embodiments, objective occurrence data 70 a may beacquired from one or more third parties 50. Examples of third parties 50include, for example, other users, medical entities such as medical ordental clinics and hospitals, content providers, employers, fitnesscenters, social organizations, and so forth.

In some embodiments, objective occurrence data 70 b may be acquired fromone or more sensors 35 that may be designed for sensing or monitoringvarious aspects associated with the user 20 a (or user 20 b). Forexample, in some implementations, the one or more sensors 35 may includea global positioning system (GPS) device for determining the location ofthe user 20 a and/or a physical activity sensor for measuring physicalactivities of the user 20 a. Examples of a physical activity sensorinclude, for example, a pedometer for measuring physical activities ofthe user 20 a. In certain implementations, the one or more sensors 35may include one or more physiological sensor devices for measuringphysiological characteristics of the user 20 a. Examples ofphysiological sensor devices include, for example, a blood pressuremonitor, a heart rate monitor, a glucometer, and so forth. In someimplementations, the one or more sensors 35 may include one or moreimage capturing devices such as a video or digital camera.

In some embodiments, objective occurrence data 70 c may be acquired froma user 20 a via the mobile device 30 (or from user 20 b via userinterface 122). For these embodiments, the objective occurrence data 70c may be in the form of blog entries (e.g., microblog entries), statusreports, or other types of electronic entries (e.g., diary or calendarentries) or messages. In various implementations, the objectiveoccurrence data 70 c acquired from the user 20 a may indicate, forexample, activities (e.g., exercise or food or medicine intake)performed by the user 20 a, certain physical characteristics (e.g.,blood pressure or location) associated with the user 20 a, or otheraspects associated with the user 20 a that the user 20 a can reportobjectively. The objective occurrence data 70 c may be in the form of atext data, audio or voice data, or image data.

The computing device 10 may also be configured to solicit subjectiveuser state data 60 including data indicating occurrence of at least onesubjective user state 60 a. Such a solicitation of the subjective userstate data 60 may be prompted in response to the acquisition ofobjective occurrence data 70* and/or in response to referencing ofhistorical data 72. The solicitation of the subjective user state 60(e.g., the data indicating the occurrence of the at least one subjectiveuser state 60 a) may be made through a network interface 120 or throughthe user interface 122. As will be further described, the dataindicating the occurrence of the at least one subjective user state 60 amay be solicited from a user 20*, from a mobile device 30 (which mayalready have been provided with such data from the user 20*), or fromone or more network servers (not depicted). Such a solicitation may beaccomplished in a number of ways depending on the specific circumstances(e.g., whether the computing device 10 is a server or a local device).Examples of how subjective user state data 60 including data indicatingoccurrence of at least one subjective user state 60 a could be solicitedinclude, for example, transmitting via a network interface 120 a requestfor subjective user state data 60, indicating via a user interface 122 arequest for subjective user state data 60, configurating or activating amobile device 30 or a network server to provide such data, and so forth.

After soliciting for the subjective user state data 60, the computingdevice 10 may be configured to acquire the subjective user state data 60from one or more sources (e.g., user 20*, mobile device 30, and soforth). In various embodiments, the subjective user state data 60acquired by the computing device 10 may include data indicatingoccurrence of at least one subjective user state 60 a associated with auser 20 a (or with user 20 b in the case where the computing device 10is a local device). The acquired subjective user state data 60 mayadditionally include data indicative of occurrence of one or moreadditional subjective user states associated with the user 20 a (or user20 b) including data indicating occurrence of at least a secondsubjective user state 60 b associated with the user 20 a (or user 20 b).Note that in various implementations, the data indicating occurrence ofat least a second subjective user state 60 b may or may not have beensolicited.

In various embodiments, the data indicating occurrence of at least onesubjective user state 60 a, as well as the data indicating occurrence ofat least a second subjective user state 60 b, may be acquired in theform of blog entries (e.g., microblog entries), status reports (e.g.,social networking status reports), electronic messages (email, textmessages, instant messages, etc.) or other types of electronic messagesor documents. The data indicating occurrence of at least one subjectiveuser state 60 a and the data indicating occurrence of at least a secondsubjective user state 60 b may, in some instances, indicate the same,contrasting, or completely different subjective user states associatedwith a user 20*.

Examples of subjective user states that may be indicated by thesubjective user state data 60 include, for example, subjective mentalstates of a user 20* (e.g., user 20* is sad or angry), subjectivephysical states of the user 20* (e.g., physical or physiologicalcharacteristic of the user 20* such as the presence, absence, elevating,or easing of a stomach ache or headache), subjective overall states ofthe user 20* (e.g., user 20* is “well”), and/or other subjective userstates that only the user 20* can typically indicate.

After acquiring the subjective user state data 60 including dataindicating occurrence of at least one subjective user state 60 a and theobjective occurrence data 70* including data indicating occurrence of atleast one objective occurrence, the computing device 10 may beconfigured to correlate the acquired subjective user data 60 with theacquired objective occurrence data 70* by, for example, determiningwhether there is a sequential relationship between the one or moresubjective user states as indicated by the acquired subjective userstate data 60 and the one or more objective occurrences indicated by theacquired objective occurrence data 70*.

In some embodiments, and as will be further explained in the operationsand processes to be described herein, the computing device 10 may befurther configured to present one or more results of correlation. Invarious embodiments, the one or more correlation results 80 may bepresented to a user 20* and/or to one or more third parties 50 invarious forms (e.g., in the form of an advisory, a warning, aprediction, and so forth). The one or more third parties 50 may be otherusers (e.g., microbloggers), health care providers, advertisers, and/orcontent providers.

As illustrated in FIG. 1 b, computing device 10 may include one or morecomponents and/or sub-modules. For instance, in various embodiments,computing device 10 may include an objective occurrence data acquisitionmodule 102, a subjective user state data solicitation module 103, asubjective user state data acquisition module 104, a correlation module106, a presentation module 108, a network interface 120 (e.g., networkinterface card or NIC), a user interface 122 (e.g., a display monitor, atouchscreen, a keypad or keyboard, a mouse, an audio system including amicrophone and/or speakers, an image capturing system including digitaland/or video camera, and/or other types of interface devices), one ormore applications 126 (e.g., a web 2.0 application, a voice recognitionapplication, and/or other applications), and/or memory 140, which mayinclude historical data 72.

FIG. 2 a illustrates particular implementations of the objectiveoccurrence data acquisition module 102 of the computing device 10 ofFIG. 1 b. In brief, the objective occurrence data acquisition module 102may be designed to, among other things, acquire objective occurrencedata 70* including data indicating occurrence of at least one objectiveoccurrence. As further illustrated, objective occurrence dataacquisition module 102 may include an objective occurrence datareception module 202 for receiving the objective occurrence data 70*from a user 20*, from one or more third parties 50 (e.g., one or morethird party sources), or from one or more sensors 35.

In some implementations, the objective occurrence data reception module202 may further include a user interface data reception module 204and/or a network interface data reception module 206. In brief, and aswill be further described in the processes and operations to bedescribed herein, the user interface data reception module 204 may beconfigured to receive objective occurrence data 70* via a user interface122 (e.g., a display monitor, a keyboard, a touch screen, a mouse, akeypad, a microphone, a camera, and/or other interface devices) such asin the case where the computing device 10 is a local device to be useddirectly by a user 20 b. In contrast, the network interface datareception module 206 may be configured to receive objective occurrencedata 70* from a wireless and/or wired network 40 via a network interface120 (e.g., network interface card or NIC) such as in the case where thecomputing device 10 is a network server.

In various embodiments, the objective occurrence data acquisition module102 may include a time data acquisition module 208 for acquiring timeand/or temporal elements associated with one or more objectiveoccurrences. For these embodiments, the time and/or temporal elements(e.g., time stamps, time interval indicators, and/or temporalrelationship indicators) acquired by the time data acquisition module208 may be useful for, among other things, determining one or moresequential patterns associated with subjective user states and objectiveoccurrences as will be further described herein.

In some implementations, the time data acquisition module 208 mayinclude a time stamp acquisition module 210 for acquiring (e.g., eitherby receiving or generating) one or more time stamps associated with oneor more objective occurrences. In the same or different implementations,the time data acquisition module 208 may include a time intervalacquisition module 212 for acquiring (e.g., either by receiving orgenerating) indications of one or more time intervals associated withone or more objective occurrences. In the same or differentimplementations, the time data acquisition module 208 may include atemporal relationship acquisition module 214 for acquiring, for example,indications of temporal relationships between subjective user states andobjective occurrences. For example, acquiring an indication that anobjective occurrence such as “eating lunch” occurred before, after, orat least partially concurrently with incidence of a subjective userstate such as a “stomach ache.”

FIG. 2 b illustrates particular implementations of the subjective userstate data solicitation module 103 of the computing device 10 of FIG. 1b. The subjective user state data solicitation module 103 may beconfigured or designed to solicit, in response to acquisition ofobjective occurrence data 70* including data indicating occurrence of atleast one objective occurrence, subjective user state data 60 includingdata indicating occurrence of at least one subjective user state 60 a.In various embodiments, the subjective user state data 60 may besolicited from a user 20*, from a mobile device 30 (e.g., in the casewhere the mobile device 30 has already received such data from a user 20a), from one or more network servers (e.g., in the case where such datahas already been provided to the network servers), or from one or morethird party sources (e.g., in the case where such data has already beenprovided to the one or more third party sources such as network serviceproviders). The solicitation may be made via, for example, networkinterface 120 or via the user interface 122 (e.g., when the computingdevice 10 is a local device such as a handheld held device to be useddirectly by a user 20 b).

In various embodiments, the subjective user state data solicitationmodule 103 may be configured to solicit data indicating occurrence of atleast one subjective user state 60 a associated with a user 20* thatoccurred at a specified point in time or occurred at a specified timeinterval. In some implementations, the solicitation of the subjectiveuser state data 60 including data indicating occurrence of at least onesubjective user state 60 a by the subjective user state datasolicitation module 103 may be prompted by the acquisition of objectiveoccurrence data 70* and/or as a result of referencing historical data 72(which may be stored in memory 140).

In some implementations, referencing of the historical data 72 by thesubjective user state data solicitation module 103 may prompt thesolicitation of particular data indicating occurrence of a particular ora particular type of subjective user state associated with a user 20*.For example, in some implementations, the subjective user state datasolicitation module 103 may solicit data indicating occurrence of asubjective mental state (e.g., soliciting data that indicates thehappiness level of the user 20*), a subjective physical state (e.g.,soliciting data that indicates the level of back pain of the user 20*),or a subjective overall state (e.g., soliciting data that indicates userstatus such as “good” or “bad”) of a user 20*.

In some implementations, the historical data 72 to be referenced may bedata that may indicate a link between a subjective user state type andan objective occurrence type. In the same or different implementations,the historical data 72 to be referenced may include one or morehistorical sequential patterns associated with the user 20*, a group ofusers, or the general population. In the same or differentimplementations, the historical data 72 to be referenced may includehistorical medical data associated with the user 20*, associated withother users, or associated with the general population. The relevance ofthe historical data 72 with respect to the solicitation operationsperformed by the subjective user state data solicitation module 103 willbe apparent in the processes and operations to be described herein.

In order to perform the various functions described herein, thesubjective user state data solicitation module 103 may include, amongother things, a network interface solicitation module 215, a userinterface solicitation module 216, a requesting module 217, aconfiguration module 218, and/or a directing/instructing module 219. Inbrief, the network interface solicitation module 215 may be employed inorder to solicit subjective user state data 60 via a network interface120. In some implementations, the network interface solicitation module215 may further include a transmission module 220 for transmitting arequest for subjective user state data 60 including data indicatingoccurrence of at least one subjective user state 60 a.

In contrast, the user interface solicitation module 216 may be employedin order to, among other things, solicit subjective user state data 60via user interface 122 from, for example, a user 20 b. In someimplementations, the user interface solicitation module 216 may furtherinclude an indication module 221 for, for example, audioally or visuallyindicating via a user interface 122 (e.g., an audio system including aspeaker and/or a display system such as a display monitor) a request forsubjective user state data 60 including data indicating occurrence of atleast one subjective user state 60 a. The requesting module 217 may beemployed in order to, among other things, request to be provided with orto have access to subjective user state data 60 including dataindicating occurrence of at least one subjective user state 60 aassociated with a user 20*. The configuration module 218 may be employedin order to configure, for example, a mobile device 30 or one or morenetwork servers (not depicted) to provide the subjective user state data60 including the data indicating occurrence of at least one subjectiveuser state 60 a. The directing/instructing module 219 may be employed inorder to direct and/or instruct, for example, a mobile device 30 or oneor more network servers (not depicted) to provide the subjective userstate data 60 including the data indicating occurrence of at least onesubjective user state 60 a.

Referring now to FIG. 2 c illustrating particular implementations of thesubjective user state data acquisition module 104 of the computingdevice 10 of FIG. 1 b. In brief, the subjective user state dataacquisition module 104 may be designed to, among other things, acquiresubjective user state data 60 including data indicating at least onesubjective user state 60 a associated with a user 20*. In variousembodiments, the subjective user state data acquisition module 104 mayinclude a reception module 224 configured to receive subjective userstate data 60. In some embodiments, the reception module 224 may furtherinclude a subjective user state data user interface reception module 226for receiving, via a user interface 122, subjective user state data 60.In the same or different embodiments, the reception module 224 mayinclude a subjective user state data network interface reception module227 for receiving, via a network interface 120, subjective user statedata 60.

In various embodiments, the subjective user state data acquisitionmodule 104 may include a time data acquisition module 228 configured toacquire (e.g., receive or generate) time and/or temporal elementsassociated with one or more subjective user states associated with auser 20*. For these embodiments, the time and/or temporal elements(e.g., time stamps, time intervals, and/or temporal relationships) maybe useful for determining sequential patterns associated with objectiveoccurrences and subjective user states.

In some implementations, the time data acquisition module 228 mayinclude a time stamp acquisition module 230 for acquiring (e.g., eitherby receiving or by generating) one or more time stamps associated withone or more subjective user states associated with a user 20*. In thesame or different implementations, the time data acquisition module 228may include a time interval acquisition module 231 for acquiring (e.g.,either by receiving or generating) indications of one or more timeintervals associated with one or more subjective user states associatedwith a user 20*. In the same or different implementations, the time dataacquisition module 228 may include a temporal relationship acquisitionmodule 232 for acquiring indications of temporal relationships betweenobjective occurrences and subjective user states (e.g., an indicationthat a subjective user state associated with a user 20* occurred before,after, or at least partially concurrently with incidence of an objectiveoccurrence).

Turning now to FIG. 2 d illustrating particular implementations of thecorrelation module 106 of the computing device 10 of FIG. 1 b. Thecorrelation module 106 may be configured to, among other things,correlate subjective user state data 60 with objective occurrence data70* based, at least in part, on a determination of at least onesequential pattern of at least one objective occurrence and at least onesubjective user state. In various embodiments, the correlation module106 may include a sequential pattern determination module 236 configuredto determine one or more sequential patterns of one or more subjectiveuser states and one or more objective occurrences.

The sequential pattern determination module 236, in variousimplementations, may include one or more sub-modules that may facilitatein the determination of one or more sequential patterns. As depicted,the one or more sub-modules that may be included in the sequentialpattern determination module 236 may include, for example, a “withinpredefined time increment determination” module 238, a temporalrelationship determination module 239, a subjective user state andobjective occurrence time difference determination module 240, and/or ahistorical data referencing module 241. In brief, the within predefinedtime increment determination module 238 may be configured to determinewhether at least one subjective user state of a user 20* occurred withina predefined time increment from an incidence of at least one objectiveoccurrence. For example, determining whether a user 20* “feeling bad”(i.e., a subjective user state) occurred within ten hours (i.e.,predefined time increment) of eating a large chocolate sundae (i.e., anobjective occurrence). Such a process may be used in order to filter outevents that are likely not related or to facilitate in determining thestrength of correlation between subjective user state data 60 andobjective occurrence data 70*. For example, if the user 20* “feelingbad” occurred more than 10 hours after eating the chocolate sundae, thenthis may indicate a weaker correlation between a subjective user state(e.g., feeling bad) and an objective occurrence (e.g., eating achocolate sundae).

The temporal relationship determination module 239 of the sequentialpattern determination module 236 may be configured to determine thetemporal relationships between one or more subjective user states andone or more objective occurrences. For example, this may entaildetermining whether a particular subjective user state (e.g., sore back)occurred before, after, or at least partially concurrently withincidence of an objective occurrence (e.g., sub-freezing temperature).

The subjective user state and objective occurrence time differencedetermination module 240 of the sequential pattern determination module236 may be configured to determine the extent of time difference betweenthe incidence of at least one subjective user state and the incidence ofat least one objective occurrence. For example, determining how longafter taking a particular brand of medication (e.g., objectiveoccurrence) did a user 20* feel “good” (e.g., subjective user state).

The historical data referencing module 241 of the sequential patterndetermination module 236 may be configured to reference historical data72 in order to facilitate in determining sequential patterns. Forexample, in various implementations, the historical data 72 that may bereferenced may include, for example, general population trends (e.g.,people having a tendency to have a hangover after drinking or ibuprofenbeing more effective than aspirin for toothaches in the generalpopulation), medical information such as genetic, metabolome, orproteome information related to the user 20* (e.g., genetic informationof the user 20* indicating that the user 20* is susceptible to aparticular subjective user state in response to occurrence of aparticular objective occurrence), or historical sequential patterns suchas known sequential patterns of the general population or of the user20* (e.g., people tending to have difficulty sleeping within five hoursafter consumption of coffee). In some instances, such historical data 72may be useful in associating one or more subjective user states with oneor more objective occurrences.

In some embodiments, the correlation module 106 may include a sequentialpattern comparison module 242. As will be further described herein, thesequential pattern comparison module 242 may be configured to comparetwo or more sequential patterns with each other to determine, forexample, whether the sequential patterns at least substantially matcheach other or to determine whether the sequential patterns arecontrasting sequential patterns.

As depicted in FIG. 2 d, in various implementations, the sequentialpattern comparison module 242 may further include one or moresub-modules that may be employed in order to, for example, facilitate inthe comparison of different sequential patterns. For example, in variousimplementations, the sequential pattern comparison module 242 mayinclude one or more of a subjective user state equivalence determinationmodule 243, an objective occurrence equivalence determination module244, a subjective user state contrast determination module 245, anobjective occurrence contrast determination module 246, a temporalrelationship comparison module 247, and/or an extent of time differencecomparison module 248.

The subjective user state equivalence determination module 243 of thesequential pattern comparison module 242 may be configured to determinewhether subjective user states associated with different sequentialpatterns are equivalent. For example, the subjective user stateequivalence determination module 243 may determine whether a firstsubjective user state of a first sequential pattern is equivalent to asecond subjective user state of a second sequential pattern. Forinstance, suppose a user 20* reports that on Monday he had a stomachache (e.g., first subjective user state) after eating at a particularrestaurant (e.g., a first objective occurrence), and suppose furtherthat the user 20* again reports having a stomach ache (e.g., a secondsubjective user state) after eating at the same restaurant (e.g., asecond objective occurrence) on Tuesday, then the subjective user stateequivalence determination module 243 may be employed in order to comparethe first subjective user state (e.g., stomach ache) with the secondsubjective user state (e.g., stomach ache) to determine whether they areequivalent.

In contrast, the objective occurrence equivalence determination module244 of the sequential pattern comparison module 242 may be configured todetermine whether objective occurrences of different sequential patternsare equivalent. For example, the objective occurrence equivalencedetermination module 244 may determine whether a first objectiveoccurrence of a first sequential pattern is equivalent to a secondobjective occurrence of a second sequential pattern. For instance, forthe above example the objective occurrence equivalence determinationmodule 244 may compare eating at the particular restaurant on Monday(e.g., first objective occurrence) with eating at the same restaurant onTuesday (e.g., second objective occurrence) in order to determinewhether the first objective occurrence is equivalent to the secondobjective occurrence.

In some implementations, the sequential pattern comparison module 242may include a subjective user state contrast determination module 245that may be configured to determine whether subjective user statesassociated with different sequential patterns are contrasting subjectiveuser states. For example, the subjective user state contrastdetermination module 245 may determine whether a first subjective userstate of a first sequential pattern is a contrasting subjective userstate from a second subjective user state of a second sequentialpattern. To illustrate, suppose a user 20* reports that he felt very“good” (e.g., first subjective user state) after jogging for an hour(e.g., first objective occurrence) on Monday, but reports that he felt“bad” (e.g., second subjective user state) when he did not exercise(e.g., second objective occurrence) on Tuesday, then the subjective userstate contrast determination module 245 may compare the first subjectiveuser state (e.g., feeling good) with the second subjective user state(e.g., feeling bad) to determine that they are contrasting subjectiveuser states.

In some implementations, the sequential pattern comparison module 242may include an objective occurrence contrast determination module 246that may be configured to determine whether objective occurrences ofdifferent sequential patterns are contrasting objective occurrences. Forexample, the objective occurrence contrast determination module 246 maydetermine whether a first objective occurrence of a first sequentialpattern is a contrasting objective occurrence from a second objectiveoccurrence of a second sequential pattern. For instance, for the aboveexample, the objective occurrence contrast determination module 246 maycompare the “jogging” on Monday (e.g., first objective occurrence) withthe “no jogging” on Tuesday (e.g., second objective occurrence) in orderto determine whether the first objective occurrence is a contrastingobjective occurrence from the second objective occurrence. Based on thecontrast determination, an inference may be made that the user 20* mayfeel better by jogging rather than by not jogging at all.

In some embodiments, the sequential pattern comparison module 242 mayinclude a temporal relationship comparison module 247 that may beconfigured to make comparisons between different temporal relationshipsof different sequential patterns. For example, the temporal relationshipcomparison module 247 may compare a first temporal relationship betweena first subjective user state and a first objective occurrence of afirst sequential pattern with a second temporal relationship between asecond subjective user state and a second objective occurrence of asecond sequential pattern in order to determine whether the firsttemporal relationship at least substantially matches the second temporalrelationship.

For example, suppose in the above example the user 20* eating at theparticular restaurant (e.g., first objective occurrence) and thesubsequent stomach ache (e.g., first subjective user state) on Mondayrepresents a first sequential pattern while the user 20* eating at thesame restaurant (e.g., second objective occurrence) and the subsequentstomach ache (e.g., second subjective user state) on Tuesday representsa second sequential pattern. In this example, the occurrence of thestomach ache after (rather than before or concurrently) eating at theparticular restaurant on Monday represents a first temporal relationshipassociated with the first sequential pattern while the occurrence of asecond stomach ache after (rather than before or concurrently) eating atthe same restaurant on Tuesday represents a second temporal relationshipassociated with the second sequential pattern. Under such circumstances,the temporal relationship comparison module 247 may compare the firsttemporal relationship to the second temporal relationship in order todetermine whether the first temporal relationship and the secondtemporal relationship at least substantially match (e.g., stomachachesin both temporal relationships occurring after eating at therestaurant). Such a match may result in the inference that a stomachache is associated with eating at the particular restaurant.

In some implementations, the sequential pattern comparison module 242may include an extent of time difference comparison module 248 that maybe configured to compare the extent of time differences betweenincidences of subjective user states and incidences of objectiveoccurrences of different sequential patterns. For example, the extent oftime difference comparison module 248 may compare the extent of timedifference between incidence of a first subjective user state andincidence of a first objective occurrence of a first sequential patternwith the extent of time difference between incidence of a secondsubjective user state and incidence of a second objective occurrence ofa second sequential pattern. In some implementations, the comparisonsmay be made in order to determine that the extent of time differences ofthe different sequential patterns at least substantially or proximatelymatch.

In some embodiments, the correlation module 106 may include a strengthof correlation determination module 250 for determining a strength ofcorrelation between subjective user state data 60 and objectiveoccurrence data 70* associated with a user 20*. In some implementations,the strength of correlation maybe determined based, at least in part, onthe results provided by the other sub-modules of the correlation module106 (e.g., the sequential pattern determination module 236, thesequential pattern comparison module 242, and their sub-modules).

FIG. 2 e illustrates particular implementations of the presentationmodule 108 of the computing device 10 of FIG. 1 b. In variousimplementations, the presentation module 108 may be configured topresent, for example, one or more results of the correlation operationsperformed by the correlation module 106. The one or more results may bepresented in different ways in various alternative embodiments. Forexample, in some implementations, the presentation of the one or moreresults may entail the presentation module 108 presenting to the user20* (or some other third party 50) an indication of a sequentialrelationship between a subjective user state and an objective occurrenceassociated with the user 20* (e.g., ″whenever you eat a banana, you havea stomach ache). In alternative implementations, other ways ofpresenting the results of the correlation may be employed. For example,in various alternative implementations, a notification may be providedto notify past tendencies or patterns associated with a user 20*. Insome implementations, a notification of a possible future outcome may beprovided. In other implementations, a recommendation for a future courseof action based on past patterns may be provided. These and other waysof presenting the correlation results will be described in the processesand operations to be described herein.

In various implementations, the presentation module 108 may include anetwork interface transmission module 252 for transmitting one or moreresults of the correlation performed by the correlation module 106 vianetwork interface 120. For example, in the case where the computingdevice 10 is a server, the network interface transmission module 252 maybe configured to transmit to the user 20 a or a third party 50 the oneor more results of the correlation performed by the correlation module106 via a network interface 120.

In the same or different implementations, the presentation module 108may include a user interface indication module 254 for indicating theone or more results of the correlation operations performed by thecorrelation module 106 via a user interface 122. For example, in thecase where the computing device 10 is a local device, the user interfaceindication module 254 may be configured to indicate to a user 20 b theone or more results of the correlation performed by the correlationmodule 106 via a user interface 122 (e.g., a display monitor, atouchscreen, an audio system including at least a speaker, and/or otherinterface devices).

The presentation module 108 may further include one or more sub-modulesto present the one or more results of the correlation operationsperformed by the correlation module 106 in different forms. For example,in some implementations, the presentation module 108 may include asequential relationship presentation module 256 configured to present anindication of a sequential relationship between at least one subjectiveuser state of a user 20* and at least one objective occurrence. In thesame or different implementations, the presentation module 108 mayinclude a prediction presentation module 258 configured to present aprediction of a future subjective user state of a user 20* resultingfrom a future objective occurrence associated with the user 20*. In thesame or different implementations, the prediction presentation module258 may also be designed to present a prediction of a future subjectiveuser state of a user 20* resulting from a past objective occurrenceassociated with the user 20*. In some implementations, the presentationmodule 108 may include a past presentation module 260 that is designedto present a past subjective user state of a user 20* in connection witha past objective occurrence associated with the user 20*.

In some implementations, the presentation module 108 may include arecommendation module 262 configured to present a recommendation for afuture action based, at least in part, on the results of a correlationof subjective user state data 60 with objective occurrence data 70* asperformed by the correlation module 106. In certain implementations, therecommendation module 262 may further include a justification module 264for presenting a justification for the recommendation presented by therecommendation module 262. In some implementations, the presentationmodule 108 may include a strength of correlation presentation module 266for presenting an indication of a strength of correlation betweensubjective user state data 60 and objective occurrence data 70*.

In various embodiments, the computing device 10 of FIG. 1 b may includea network interface 120 that may facilitate in communicating with a user20 a, with one or more sensors 35, and/or with one or more third parties50. For example, in embodiments where the computing device 10 is aserver, the computing device 10 may include a network interface 120 thatmay be configured to receive from the user 20 a subjective user statedata 60. In some embodiments, objective occurrence data 70 a, 70 b,and/or 70 c may also be received through the network interface 120.Examples of a network interface 120 includes, for example, a networkinterface card (NIC).

The computing device 10 may also include a memory 140 for storingvarious data. For example, in some embodiments, memory 140 may beemployed in order to store historical data 72. In some implementations,the historical data 72 may include historical subjective user state dataof a user 20* that may indicate one or more past subjective user statesof the user 20* and historical objective occurrence data that mayindicate one or more past objective occurrences. In same or differentimplementations, the historical data 72 may include historical medicaldata of a user 20* (e.g., genetic, metoblome, proteome information),population trends, historical sequential patterns derived from generalpopulation, and so forth.

In various embodiments, the computing device 10 may include a userinterface 122 to communicate directly with a user 20 b. For example, inembodiments in which the computing device 10 is a local device such as ahandheld device (e.g., cellular telephone, PDA, and so forth), the userinterface 122 may be configured to directly receive from the user 20 bsubjective user state data 60 and/or objective occurrence data 70*. Insome implementations, the user interface 122 may also be designed tovisually or audioally present the results of correlating subjective userstate data 60 and objective occurrence data 70*. The user interface 122may include, for example, one or more of a display monitor, a touchscreen, a key board, a key pad, a mouse, an audio system including amicrophone and/or one or more speakers, an imaging system including adigital or video camera, and/or other user interface devices.

FIG. 2 e illustrates particular implementations of the one or moreapplications 126 of FIG. 1 b. For these implementations, the one or moreapplications 126 may include, for example, one or more communicationapplications 267 such as a text messaging application and/or an audiomessaging application including a voice recognition system application.In some implementations, the one or more applications 126 may include aweb 2.0 application 268 to facilitate communication via, for example,the World Wide Web. The functional roles of the various components,modules, and sub-modules of the computing device 10 presented thus farwill be described in greater detail with respect to the processes andoperations to be described herein. Note that the subjective user statedata 60 may be in a variety of forms including, for example, textmessages (e.g., blog entries, microblog entries, instant messages, textemail messages, and so forth), audio messages, and/or images (e.g., animage capturing user's facial expression or gestures).

FIG. 3 illustrates an operational flow 300 representing exampleoperations related to, among other things, solicitation and acquisitionof subjective user state data 60 in response to acquisition of objectiveoccurrence data 70* in accordance with various embodiments. In someembodiments, the operational flow 300 may be executed by, for example,the computing device 10 of FIG. 1 b.

In FIG. 3 and in the following figures that include various examples ofoperational flows, discussions and explanations may be provided withrespect to the above-described exemplary environment of FIGS. 1 a and 1b, and/or with respect to other examples (e.g., as provided in FIGS. 2a-2 f) and contexts. However, it should be understood that theoperational flows may be executed in a number of other environments andcontexts, and/or in modified versions of FIGS. 1 a, 1 b, and 2 a-2 f.Also, although the various operational flows are presented in thesequence(s) illustrated, it should be understood that the variousoperations may be performed in other orders than those which areillustrated, or may be performed concurrently.

Further, in FIG. 3 and in following figures, various operations may bedepicted in a box-within-a-box manner. Such depictions may indicate thatan operation in an internal box may comprise an optional exampleembodiment of the operational step illustrated in one or more externalboxes. However, it should be understood that internal box operations maybe viewed as independent operations separate from any associatedexternal boxes and may be performed in any sequence with respect to allother illustrated operations, or may be performed concurrently.

In any event, after a start operation, the operational flow 300 may moveto an objective occurrence data acquisition operation 302 for acquiringobjective occurrence data including data indicating occurrence of atleast one objective occurrence. For instance, the objective occurrencedata acquisition module 102 of the computing device 10 acquiring (e.g.,receiving via network interface 120 or via user interface 122) objectiveoccurrence data 70* including data indicating occurrence of at least oneobjective occurrence (e.g., an activity performed by a user 20*, anactivity performed by another user (not depicted), a physicalcharacteristic of the user 20*, an external event, and so forth).

Operational flow 300 may also include a subjective user state datasolicitation operation 304 for soliciting, in response to theacquisition of the objective occurrence data, subjective user state dataincluding data indicating occurrence of at least one subjective userstate associated with a user. For instance, the subjective user statedata solicitation module 103 of the computing device 10 soliciting(e.g., requesting from the user 20*, from the mobile device 30, or froma network server), in response to the acquisition of the objectiveoccurrence data 70*, subjective user state data 60 including dataindicating occurrence of at least one subjective user state 60 a (e.g.,a subjective mental state, a subjective physical state, or a subjectiveoverall state) associated with a user 20*.

Note that the solicitation of the subjective user state data 60, asdescribed above, may or may not be in reference to solicitation ofparticular data that indicates occurrence of a particular or particulartype of subjective user state. That is, in some embodiments, thesolicitation of the subjective user state data 60 may be in reference tosolicitation for subjective user state data 60 including data indicatingoccurrence of any subjective user state, while in other embodiments, thesolicitation of the subjective user state data 60 may involvesolicitation for subjective user state data 60 including data indicatingoccurrence of a particular or particular type of subjective user state.

The term “soliciting” as described above may be in reference to director indirect solicitation of (e.g., requesting to be provided with,requesting to access, or other methods of being provided with, or beingallowed access) subjective user state data 60 from one or more sources.The sources may be the user 20* him or herself, a mobile device 30, orone or more network servers (not depicted), which may have already beenprovided with such subjective user state data 60. For example, if thecomputing device 10 is a server, then the computing device 10 mayindirectly solicit the objective occurrence data 70* from a user 20 a bytransmitting the solicitation (e.g., a request or inquiry) to the mobiledevice 30, which may then actually solicit the subjective user statedata 60 from the user 20 a. Alternatively, such subjective user statedata 60 may have already been provided to the mobile device 30, in whichcase the mobile device 30 merely provides for or allows access to suchdata. In still other alternative implementations, such subjective userstate data 60 may have been previously stored in a network server (notdepicted), and such a network server may be solicited for the subjectiveuser state data 60. In yet other implementations in which the computingdevice 10 is a local device such as a handheld device to be useddirectly by a user 20 b, the computing device 10 may directly solicitthe subjective user state data 60 from the user 20 b.

Operational flow 300 may further include subjective user state dataacquisition operation 306 for acquiring the subjective user state data.For instance, the subjective user state data acquisition module 104 ofthe computing device 10 acquiring (e.g., receiving via user interface122 or via the network interface 120) the subjective user state data 60.

Finally, operational flow 300 may include a correlation operation 308for correlating the subjective user state data with the objectiveoccurrence data. For instance, the correlation module 106 of thecomputing device 10 correlating the subjective user state data 60 withthe objective occurrence data 70* by determining, for example, at leastone sequential pattern (e.g., time sequential pattern) associated withthe occurrence of the at least one subjective user state (e.g., userfeeling “tired”) and the occurrence of the at least one objectiveoccurrence (e.g., elevated blood sugar level).

In various implementations, the objective occurrence data acquisitionoperation 302 of FIG. 3 may include one or more additional operations asillustrated in FIGS. 4 a, 4 b, and 4 c. For example, in someimplementations the objective occurrence data acquisition operation 302may include a reception operation 402 for receiving the objectiveoccurrence data as depicted in FIG. 4 a. For instance, the objectiveoccurrence data reception module 202 (see FIG. 2 a) of the computingdevice 10 receiving (e.g., via network interface 120 or via the userinterface 122) the objective occurrence data 70*.

The reception operation 402 in turn may further include one or moreadditional operations. For example, in some implementations, thereception operation 402 may include an operation 404 for receiving theobjective occurrence data from at least one of a wireless network or awired network as depicted in FIG. 4 a. For instance, the networkinterface data reception module 206 (see FIG. 2 a) of the computingdevice 10 receiving the objective occurrence data 70* from a wirelessand/or wired network 40 via a network interface 120 (e.g., networkinterface card or “NIC”).

In some implementations, the reception operation 402 may include anoperation 406 for receiving the objective occurrence data via one ormore blog entries as depicted in FIG. 4 a. For instance, the objectiveoccurrence data reception module 202 of the computing device 10receiving (e.g., through a network interface 120 or through a userinterface 122) the objective occurrence data 70 a or 70 c via one ormore blog entries (e.g., microblog entries).

In some implementations, the reception operation 402 may include anoperation 408 for receiving the objective occurrence data via one ormore status reports as depicted in FIG. 4 a. For instance, the objectiveoccurrence data reception module 202 of the computing device 10receiving (e.g., through the network interface 120 or through the userinterface 122) the objective occurrence data 70 a or 70 c via one ormore status reports (e.g., social networking site status reports).

In some implementations, the reception operation 402 may include anoperation 410 for receiving the objective occurrence data from one ormore third party sources as depicted in FIG. 4 a. For instance, theobjective occurrence data reception module 202 of the computing device10 receiving (e.g., through the network interface 120) the objectiveoccurrence data 70 a from one or more third party sources (e.g., otherusers, healthcare entities such as medical or dental clinics, hospitals,athletic gyms, content providers, and so forth).

In some implementations, the reception operation 402 may include anoperation 412 for receiving the objective occurrence data from one ormore sensors configured to sense one or more objective occurrences asdepicted in FIG. 4 a. For instance, the objective occurrence datareception module 202 of the computing device 10 receiving (e.g., throughthe network interface 120) the objective occurrence data 70 b from oneor more sensors 35 (e.g., one or more physiological sensors such asglucometers and blood pressure devices, pedometer, GPS, and so forth)configured to sense one or more objective occurrences (e.g., one or morephysiological characteristics of user 20 a, one or more physicalactivities of the user 20 a, and/or one or more locations of user 20 a).

In some implementations, the reception operation 402 may include anoperation 414 for receiving the objective occurrence data from the useras depicted in FIG. 4 a. For instance, the objective occurrence datareception module 202 of the computing device 10 receiving (e.g., throughthe network interface 120 or through the user interface 122) theobjective occurrence data 70 c from the user 20*.

The objective occurrence data acquisition operation 302 of FIG. 3 may,in various implementations, include an operation 416 for acquiring atime stamp associated with occurrence of the at least one objectiveoccurrence as depicted in FIG. 4 a. For instance, the time stampacquisition module 210 of the computing device 10 acquiring (e.g., viathe network interface 120, via the user interface 122 as provided by theuser 20*, or by self or automatically generating) a time stampassociated with occurrence of the at least one objective occurrence(e.g., a physical characteristic of the user 20*, one or more locationsassociated with the user 20*, an activity executed by the user 20* or byothers, an external event such as local weather, or some otherobjectively observable occurrence).

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 418 for acquiring an indicationof a time interval associated with occurrence of the at least oneobjective occurrence as depicted in FIG. 4 a. For instance, the timeinterval acquisition module 212 of the computing device 10 acquiring(e.g., via the network interface 120, via the user interface 122 asprovided by the user 20*, or by self or automatically generating) anindication of a time interval associated with occurrence of the at leastone objective occurrence.

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 420 for acquiring an indicationof a temporal relationship between occurrence of the at least oneobjective occurrence and occurrence of at least one subjective userstate as depicted in FIG. 4 b. For instance, the temporal relationshipacquisition module 214 of the computing device 10 acquiring (e.g., viathe network interface 120, via the user interface 122 as provided by theuser 20*, or by automatically generating) an indication of at least atemporal relationship (e.g., before, after, or at least partiallyconcurrently) between occurrence of the at least one objectiveoccurrence (e.g., staying up late) and occurrence of the at least onesubjective user state (e.g., headache).

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 422 for acquiring data indicatingthe at least one objective occurrence and one or more attributesassociated with the at least one objective occurrence as depicted inFIG. 4 b. For instance, the objective occurrence data reception module202 of the computing device 10 acquiring data indicating the at leastone objective occurrence (e.g., ingestion of a medicine or food item)and one or more attributes (e.g., quality, quantity, brand, and/orsource of the medicine or food item ingested) associated with the atleast one objective occurrence.

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 424 for acquiring data indicatingat least one objective occurrence of an ingestion by the user of amedicine as depicted in FIG. 4 b. For instance, the objective occurrencedata acquisition module 102 of the computing device 10 acquiring (e.g.,via the network interface 120 or via the user interface 122) dataindicating at least one objective occurrence of an ingestion by the user20* of a medicine (e.g., a dosage of a beta blocker).

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 426 for acquiring data indicatingat least one objective occurrence of an ingestion by the user of a fooditem as depicted in FIG. 4 b. For instance, the objective occurrencedata acquisition module 102 of the computing device 10 acquiring (e.g.,via the network interface 120 or via the user interface 122) dataindicating at least one objective occurrence of an ingestion by the user20* of a food item (e.g., an orange).

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 428 for acquiring data indicatingat least one objective occurrence of an ingestion by the user of anutraceutical as depicted in FIG. 4 b. For instance, the objectiveoccurrence data acquisition module 102 of the computing device 10acquiring (e.g., via the network interface 120 or via the user interface122) data indicating at least one objective occurrence of an ingestionby the user 20* of a nutraceutical (e.g. broccoli).

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 430 for acquiring data indicatingat least one objective occurrence of an exercise routine executed by theuser as depicted in FIG. 4 b. For instance, the objective occurrencedata acquisition module 102 of the computing device 10 acquiring (e.g.,via the network interface 120 or via the user interface 122) dataindicating at least one objective occurrence of an exercise routine(e.g., working out on a exercise machine such as a treadmill) executedby the user 20*.

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 432 for acquiring data indicatingat least one objective occurrence of a social activity executed by theuser as depicted in FIG. 4 c. For instance, the objective occurrencedata acquisition module 102 of the computing device 10 acquiring (e.g.,via the network interface 120 or via the user interface 122) dataindicating at least one objective occurrence of a social activity (e.g.,hiking or skiing with friends, dates, dinners, and so forth) executed bythe user 20*.

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 434 for acquiring data indicatingat least one objective occurrence of an activity performed by a thirdparty as depicted in FIG. 4 c. For instance, the objective occurrencedata acquisition module 102 of the computing device 10 acquiring (e.g.,via the network interface 120 or via the user interface 122) dataindicating at least one objective occurrence of an activity (e.g., bosson a vacation) performed by a third party 50.

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 436 for acquiring data indicatingat least one objective occurrence of a physical characteristic of theuser as depicted in FIG. 4 c. For instance, the objective occurrencedata acquisition module 102 of the computing device 10 acquiring (e.g.,via the network interface 120 or via the user interface 122) dataindicating at least one objective occurrence of a physicalcharacteristic (e.g., a blood sugar level) of the user 20*. Note that aphysical characteristic such as a blood sugar level could be determinedusing a device such as a glucometer and then reported by the user 20*,by a third party 50, or by the device (e.g., glucometer) itself.

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 438 for acquiring data indicatingat least one objective occurrence of a resting, a learning or arecreational activity by the user as depicted in FIG. 4 c. For instance,the objective occurrence data acquisition module 102 of the computingdevice 10 acquiring (e.g., via the network interface 120 or via the userinterface 122) data indicating at least one objective occurrence of aresting (e.g., sleeping), a learning (e.g., reading), or a recreationalactivity (e.g., a round of golf) by the user 20*.

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 440 for acquiring data indicatingat least one objective occurrence of an external event as depicted inFIG. 4 c. For instance, the objective occurrence data acquisition module102 of the computing device 10 acquiring (e.g., via the networkinterface 120 or via the user interface 122) data indicating at leastone objective occurrence of an external event (e.g., rain storm).Examples of external events include, for example, the weather,performance of the stock market, air quality level, and/or any otherevents that may or may not be of interest to a user 20*.

In some implementations, the objective occurrence data acquisitionoperation 302 may include an operation 442 for acquiring data indicatingat least one objective occurrence related to a location of the user asdepicted in FIG. 4 c. For instance, the objective occurrence dataacquisition module 102 of the computing device 10 acquiring (e.g., viathe network interface 120 or via the user interface 122) data indicatingat least one objective occurrence related to a location (e.g., workoffice at a point or interval in time) of the user 20*. In someinstances, such data may be provided by the user 20* via the userinterface 122 (e.g., in the case where the computing device 10 is alocal device) or via the mobile device 30 (e.g., in the case where thecomputing device 10 is a network server). Alternatively, such data maybe provided directly by a sensor device 35 such as a GPS device, or by athird party 50.

Referring back to FIG. 3, the subjective user state data solicitationoperation 304 in various embodiments may include one or more additionaloperations as illustrated in FIGS. 5 a to 5 d. For example, in someimplementations, the subjective user state data solicitation operation304 may include an operation 500 for requesting for subjective userstate data including the data indicating occurrence of at least onesubjective user state associated with a user as depicted in FIG. 5 a.For instance, the requesting module 217 (see FIG. 2 b) of the computingdevice 10 requesting (e.g., transmitting a request via a networkinterface 120 or indicating a request via a user interface 122) forsubjective user state data 60 including the data indicating occurrenceof at least one subjective user state 60 a (e.g., subjective mentalstate, subjective physical state, or subjective overall state)associated with a user 20*.

In some implementations, operation 500 may further include an operation502 for requesting to be provided with the data indicating occurrence ofat least one subjective user state associated with a user as depicted inFIG. 5 a. For instance, the requesting module 217 (see FIG. 2 b) of thecomputing device 10 requesting (e.g., transmitting a request via anetwork interface 120 or indicating a request via a user interface 122)to be provided with the data indicating occurrence of at least onesubjective user state 60 a associated with a user 20*. In someinstances, this may involve asking a user 20*, a mobile device 30, or athird party source such as a network server (not depicted) to providethe data indicating occurrence of at least one subjective user state 60a associated with the user 20*.

In some implementations, operation 500 may include an operation 504 forrequesting to have access to the data indicating occurrence of at leastone subjective user state associated with a user as depicted in FIG. 5a. For instance, the requesting module 217 (see FIG. 2 b) of thecomputing device 10 requesting (e.g., asking a mobile device 30 and/or athird party source such as a network server) to have access to the dataindicating occurrence of at least one subjective user state 60 aassociated with a user 20 a.

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 506 for configuring to obtain thedata indicating occurrence of at least one subjective user stateassociated with a user as depicted in FIG. 5 a. For instance, theconfiguration module 218 of the computing device 10 configuring (e.g., amobile device 30 or a network server) to obtain the data indicatingoccurrence of at least one subjective user state 60 a (e.g., subjectivemental state, subjective physical state, or subjective overall state)associated with a user 20 a.

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 508 for directing or instructingto obtain the data indicating occurrence of at least one subjective userstate associated with a user as depicted in FIG. 5 a. For instance, thedirecting/instructing module 219 directing or instructing (e.g.,directing or instructing a mobile device 30 or a network server) toobtain the data indicating occurrence of at least one subjective userstate 60 a (e.g., subjective mental state, subjective physical state, orsubjective overall state) associated with a user 20 a. That is, a mobiledevice 30 or a network server, for example, may be instructed ordirected to provide (e.g., allow access or to supply or transmit) thedata indicating occurrence of the at least one subjective user state 60a associated with the user 20 a.

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 510 for soliciting from the userthe data indicating occurrence of at least one subjective user stateassociated with the user as depicted in FIG. 5 a. For instance, thesubjective user state data solicitation module 103 of the computingdevice 10 soliciting (e.g., via user interface 122 or via networkinterface 120) from the user 20* the data indicating occurrence of atleast one subjective user state 60 a (e.g., subjective mental state,subjective physical state, or subjective overall state) associated withthe user 20*.

Operation 510, in turn, may further include an operation 512 forsoliciting the data indicating occurrence of at least one subjectiveuser state associated with the user via a user interface as depicted inFIG. 5 a. For instance, the user interface solicitation module 216 ofthe computing device 10 soliciting (e.g., audioally or visuallyrequesting through an audio system or a display system) the dataindicating occurrence of at least one subjective user state 60 a (e.g.,subjective mental state, subjective physical state, or subjectiveoverall state) associated with the user 20 b via a user interface 122.

In various implementations, operation 512 may include an operation 514for indicating a request for the data indicating occurrence of at leastone subjective user state associated with the user through at least oneof a display monitor or a touchscreen as depicted in FIG. 5 a. Forinstance, the indication module 221 of the computing device 10 visuallyindicating a request for the data indicating occurrence of at least onesubjective user state 60 a (e.g., subjective mental state, subjectivephysical state, or subjective overall state) associated with the user 20b through at least one of a display monitor or a touchscreen.

In some implementations, operation 512 may include an operation 516 forindicating a request for the data indicating occurrence of at least onesubjective user state associated with the user through at least an audiosystem as depicted in FIG. 5 a. For instance, the indication module 221of the computing device 10 audioally indicating a request for the dataindicating occurrence of at least one subjective user state 60 a (e.g.,subjective mental state, subjective physical state, or subjectiveoverall state) associated with the user 20 b through at least an audiosystem.

In various implementations, operation 510 of FIG. 5 a may also includean operation 518 for soliciting the data indicating occurrence of atleast one subjective user state associated with the user via a networkinterface as depicted in FIG. 5 b. For instance, the network interfacesolicitation module 215 soliciting (e.g., transmitting a request forsupplying or a request to access) the data indicating occurrence of atleast one subjective user state 60 a (e.g., subjective mental state,subjective physical state, or subjective overall state) associated withthe user 20 a via a network interface 120.

Operation 518, in some implementations, may further include an operation520 for transmitting to the user a request for the data indicatingoccurrence of at least one subjective user state associated with theuser as depicted in FIG. 5 b. For instance, the transmission module 220of the computing device 10 transmitting to the user 20 a (e.g.,transmitting to a client device such as mobile device 30) a request forthe data indicating occurrence of at least one subjective user state 60a (e.g., subjective mental state, subjective physical state, orsubjective overall state) associated with the user 20 a.

In some implementations, operation 510 may include an operation 522 forrequesting the user to select a subjective user state from a pluralityof indicated alternative subjective user states as depicted in FIG. 5 b.For instance, the requesting module 217 of the computing device 10audioally or visually requesting the user 20* to select a subjectiveuser state (e.g., feeling hot) from a plurality of indicated alternativesubjective user states (e.g., feeling hot, feeling cold, feelingextremely cold, feeling extremely hot, feeling good, feeling bad,feeling ill, having a headache, having a stomach ache, and so forth). Insome cases, this may be accomplished by, for example, displaying via adisplay monitor or a touchscreen a list of different subjective userstates that the user 20* can select from.

Operation 522, in turn, may further include an operation 524 forrequesting the user to select a subjective user state from a pluralityof indicated alternative contrasting subjective user states as depictedin FIG. 5 b. For instance, the requesting module 217 of the computingdevice 10 audioally or visually requesting the user 20* to select asubjective user state (e.g., feeling very good) from a plurality ofindicated alternative contrasting subjective user states (e.g., feelingextremely happy, feeling very happy, feeling happy, feeling slightlyhappy, feeling indifferent, feeling sad, feeling very sad, and soforth).

In various implementations, operation 510 may include an operation 526for requesting the user to confirm occurrence of a subjective user stateas depicted in FIG. 5 b. For instance, the requesting module 217 of thecomputing device 10 audioally or visually requesting the user 20* toconfirm occurrence of a subjective user state (e.g., is user feelingnauseous?). In some implementations, such an operation may includeproviding other additional information to the user 20* such as “does theuser feel nauseous after drinking the beer this morning?” Note that inthis example, the consumption of the beer would be an objectiveoccurrence that may have been previously reported by the user 20*.

In some implementations, operation 510 may include an operation 528 forrequesting the user to provide an indication of occurrence of the atleast one subjective user state with respect to occurrence of the atleast one objective occurrence as depicted in FIG. 5 b. For instance,the requesting module 217 of the computing device 10 audioally orvisually requesting the user 20* to provide an indication of occurrenceof the at least one subjective user state with respect to occurrence ofthe at least one objective occurrence. As an illustration, the user 20 bmay be asked through the user interface 122 (e.g., an audio system or avisual system such as a display monitor) how the user 20 b felt, forexample, after taking a walk (e.g., an objective occurrence that mayhave been reported by the user 20 b).

In some implementations, operation 510 may include an operation 530 forrequesting the user to provide an indication of a time or temporalelement associated with occurrence of the at least one subjective userstate as depicted in FIG. 5 c. For instance, the requesting module 217of the computing device 10 audioally or visually requesting the user 20*to provide an indication of a time or temporal element (e.g., morning,afternoon, evening, before lunch, after lunch, before midnight, aftermidnight, etc.) associated with occurrence of the at least onesubjective user state (e.g., feeling gloomy). For example, a user 20*being asked through the user interface 122 or through the mobile device30 what part of the day did the user 20* feel gloomy?

Operation 530 may, in turn, include one or more additional operations.For example, in some implementations operation 530 may include anoperation 532 for requesting the user to provide an indication of apoint in time associated with the occurrence of the at least onesubjective user state as depicted in FIG. 5 c. For instance, therequesting module 217 of the computing device 10 requesting the user 20*to provide an indication of a point in time (e.g., 3 PM) associated withthe occurrence of the at least one subjective user state (e.g., userfeeling tired).

In some implementations, operation 530 may include an operation 534 forrequesting the user to provide an indication of a time intervalassociated with the occurrence of the at least one subjective user stateas depicted in FIG. 5 c. For instance, the requesting module 217 of thecomputing device 10 requesting the user 20* to provide an indication ofa time interval associated with the occurrence of the at least onesubjective user state (e.g., headache). For example, asking a user 20 b,via the user interface 122, from what time to what time did the user 20*have a headache?

In some implementations, operation 530 may include an operation 536 forrequesting the user to provide an indication of a temporal relationshipbetween occurrence of the at least one subjective user state andoccurrence of at least one objective occurrence as depicted in FIG. 5 c.For instance, the requesting module 217 of the computing device 10requesting the user 20* to provide an indication of a temporalrelationship between occurrence of the at least one subjective userstate and occurrence of at least one objective occurrence (e.g., askinga user 20* if the user 20* felt sick during, before, or after eating atthe user's favorite Latin restaurant).

In various implementations, the subjective user state data solicitationoperation 304 of FIG. 3 may include an operation 538 for soliciting dataindicating occurrence of at least one subjective mental state associatedwith the user as depicted in FIG. 5 c. For instance, the subjective userstate data solicitation module 103 of the computing device 10 soliciting(e.g., via the user interface 122 or via the network interface 120) dataindicating occurrence of at least one subjective mental state (e.g.,happiness, sadness, pessimism, optimism, pain, alertness, mentalfatigue, fatigue, love, desire, and so forth) associated with the user20*.

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 540 for soliciting dataindicating occurrence of at least one subjective physical stateassociated with the user as depicted in FIG. 5 c. For instance, thesubjective user state data solicitation module 103 of the computingdevice 10 soliciting (e.g., via the user interface 122 or via thenetwork interface 120) data indicating occurrence of at least onesubjective physical state (e.g., presence or absence of an upsetstomach, a level of physical fatigue, and so forth) associated with theuser 20*.

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 542 for soliciting dataindicating occurrence of at least one subjective overall stateassociated with the user as depicted in FIG. 5 c. For instance, thesubjective user state data solicitation module 103 of the computingdevice 10 soliciting (e.g., via the user interface 122 or via thenetwork interface 120) data indicating occurrence of at least onesubjective overall state (e.g., user is good, bad, rested, and so forth)associated with the user 20*.

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 544 for soliciting dataindicating occurrence of at least one subjective user state during aspecified point in time as depicted in FIG. 5 c. For instance, thesubjective user state data solicitation module 103 of the computingdevice 10 soliciting (e.g., via the user interface 122 or via thenetwork interface 120) data indicating occurrence of at least onesubjective user state 60 a (e.g., user wellness) that occurred during aspecified point in time. For example, asking a user 20* via the userinterface 122 or via the mobile device 30 how the user 20* felt at 6 PM.

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 546 for soliciting dataindicating occurrence of at least one subjective user state during aspecified time interval as depicted in FIG. 5 c. For instance, thesubjective user state data solicitation module 103 of the computingdevice 10 soliciting (e.g., via the user interface 122 or via thenetwork interface 120) data indicating occurrence of at least onesubjective user state 60 a that occurred during a specified timeinterval. For example, asking a user 20 b, via the user interface 122,how the user 20 b felt between 6 PM and 8 PM.

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 548 for soliciting dataindicating occurrence of the at least one subjective user state inresponse to the acquisition of the objective occurrence data and basedon historical data as depicted in FIG. 5 d. For instance, the subjectiveuser state data solicitation module 103 of the computing device 10 beingprompted to solicit (e.g., via the user interface 122 or via the networkinterface 120) data indicating occurrence of the at least one subjectiveuser state 60 a in response to the acquisition of the objectiveoccurrence data 70* and based on referencing of historical data 72.

For example, suppose the historical data 72 indicates that the last timethe user 20* ate a chocolate sundae, the user 20* had a stomach ache.Suppose further that the user 20* again reports that the user 20* ateanother chocolate sundae (e.g., objective occurrence) the next day butforgets to indicate the subjective user state of the user 20* aftereating the chocolate sundae. Then, upon the reporting of the objectiveoccurrence (e.g., eating a chocolate sundae), and based on historicaldata 72 (e.g., the previous reports of eating a chocolate sundae andhaving a stomach ache), the user 20* may be asked via the user interface122 or via the mobile device 30 how the user 20* feels or whether theuser 20* had a stomach ache after consuming the chocolate sundae.

Alternatively, a solicitation from the mobile device 30 or from anetwork server (not depicted) for data that indicates the subjectiveuser state of the user 20 a around the time of the consumption of thesecond chocolate sundae may be prompted based on the reporting of theconsumption of the second chocolate sundae and based on historical data72 without soliciting such data from the user 20 a. That is, in somecases, such data may have already been received and/or recorded by themobile device 30 or by the network server. In which case, there is noneed to solicit the data from the user 20 a and instead, the relevantdata may only need to be accessed or be prompted to be released.

In various implementations, operation 548 may include one or moreadditional operations. For example, in some implementations, operation548 may include an operation 550 for soliciting data indicatingoccurrence of the at least one subjective user state based, at least inpart, on one or more historical sequential patterns as depicted in FIG.5 d. For instance, the subjective user state data solicitation module103 of the computing device 10 being prompted to solicit (e.g., via theuser interface 122 or via the network interface 120) data indicatingoccurrence of the at least one subjective user state 60 a based, atleast in part, on one or more historical sequential patterns (e.g.,historical sequential patterns associated with the user 20*, derivedfrom general population, or from a group of users).

In some implementations, operation 548 may include an operation 552 forsoliciting data indicating occurrence of the at least one subjectiveuser state based, at least in part, on medical data associated with theuser as depicted in FIG. 5 d. For instance, the subjective user statedata solicitation module 103 of the computing device 10 being promptedto solicit (e.g., via the user interface 122 or via the networkinterface 120) data indicating occurrence of the at least one subjectiveuser state 60 a based, at least in part, on medical data (e.g., genetic,metabolome, or proteome data of the user 20*) associated with the user20*.

In some implementations, operation 548 may include an operation 554 forsoliciting data indicating occurrence of the at least one subjectiveuser state based, at least in part, on the historical data indicating alink between a subjective user state type and an objective occurrencetype as depicted in FIG. 5 d. For instance, the subjective user statedata solicitation module 103 of the computing device 10 being promptedto solicit (e.g., via the user interface 122 or via the networkinterface 120) data indicating occurrence of the at least one subjectiveuser state 60 a (e.g., feeling gloomy) based, at least in part, on thehistorical data 72 indicating a link between a subjective user statetype and an objective occurrence type (e.g., link between moods ofpeople and weather).

In some implementations, operation 548 may include an operation 556 forsoliciting data indicating occurrence of the at least one subjectiveuser state, the soliciting prompted, at least in part, by the historicaldata as depicted in FIG. 5 d. For instance, the subjective user statedata solicitation module 103 of the computing device 10 being promptedto solicit (e.g., via the user interface 122 or via the networkinterface 120) data indicating occurrence of the at least one subjectiveuser state (e.g., feeling gloomy), the soliciting prompted, at least inpart, by the historical data 72 (e.g., historical data 72 that indicatesthat the user 20* or people in the general population tend to be gloomywhen there is overcast weather).

In some implementations, operation 548 may include an operation 558 forsoliciting data indicating occurrence of a particular or a particulartype of subjective user state based on the historical data as depictedin FIG. 5 d. For instance, the subjective user state data solicitationmodule 103 of the computing device 10 being prompted to solicit (e.g.,via the user interface 122 or via the network interface 120) dataindicating occurrence of a particular or a particular type of subjectiveuser state (e.g., requesting for an indication of a subjective physicalstate of the user 20* such as requesting for an indication as to whetherthe user 20* has a stomach condition or a stomach ache) based on thehistorical data 72 (e.g., historical data 72 that links stomach aches toeating chocolate sundaes).

In some implementations, the subjective user state data solicitationoperation 304 may include an operation 560 for soliciting dataindicating one or more attributes associated with the at least onesubjective user state as depicted in FIG. 5 d. For instance, thesubjective user state data solicitation module 103 of the computingdevice 10 being prompted to solicit (e.g., via the user interface 122 orvia the network interface 120) data indicating one or more attributesassociated with the at least one subjective user state (e.g., intensityor length of pain).

In various embodiments, the subjective user state data acquisitionoperation 306 of FIG. 3 may include one or more additional operations asillustrated in FIGS. 6 a to 6 c. For example, in some implementations,the subjective user state data acquisition operation 306 may include anoperation 602 for receiving the subjective user state data via a userinterface as depicted in FIG. 6 a. For instance, the subjective userstate data user interface reception module 226 (see FIG. 2 c) of thecomputing device 10 receiving the subjective user state data 60 via auser interface 122 (e.g., a key pad, a touchscreen, a mouse, an audiosystem including a microphone, an image capturing system such as adigital or video camera, or other user interface devices).

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 604 for receiving the subjectiveuser state data via a network interface as depicted in FIG. 6 a. Forinstance, the subjective user state data network interface receptionmodule 227 of the computing device 10 receiving the subjective userstate data 60 (e.g., in the form of text data, audio data, or imagedata) via a network interface 120 (e.g., network interface card or“NIC”).

Operation 604 may, in turn, include one or more additional operations invarious alternative implementations. For example, in someimplementations, operation 604 may include an operation 606 forreceiving data indicating the at least one subjective user state via anelectronic message generated by the user as depicted in FIG. 6 a. Forinstance, the subjective user state data network interface receptionmodule 227 of the computing device 10 receiving (e.g., via networkinterface 120) data indicating the at least one subjective user state 60a via an electronic message (e.g., email, instant message, text message,and so forth) generated, at least in part, by the user 20 a.

In some implementations, operation 604 may include an operation 608 forreceiving data indicating the at least one subjective user state via ablog entry generated by the user as depicted in FIG. 6 a. For instance,the subjective user state data network interface reception module 227 ofthe computing device 10 receiving (e.g., via network interface 120) dataindicating the at least one subjective user state via one or more blogentries (e.g., microblog entry) generated, at least in part, by the user20 a.

In some implementations, operation 604 may include an operation 610 forreceiving data indicating the at least one subjective user state via astatus report generated by the user as depicted in FIG. 6 a. Forinstance, the subjective user state data network interface receptionmodule 227 of the computing device 10 receiving (e.g., via networkinterface 120) data indicating the at least one subjective user statevia one or more status reports (e.g., social networking status report)generated, at least in part, by the user 20 a.

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 612 for receiving subjective userstate data including data indicating at least one subjective user statespecified by a selection made by the user, the selection being aselection of a subjective user state from a plurality of indicatedalternative subjective user states as depicted in FIG. 6 a. Forinstance, the reception module 224 (see FIG. 2 c) of the computingdevice 10 receiving subjective user state data 60 including dataindicating at least one subjective user state 60 a specified by aselection made by the user 20*, the selection being a selection of asubjective user state from a plurality of indicated alternativesubjective user states (e.g., as indicated by the user interface 122 orby the mobile device 30). For example, user 20 b may be allowed toselect a subjective user state from a list of alternative subjectiveuser states (e.g., feeling well, feeling sore, feeling sad, having aheadache, and so forth) displayed by a display monitor (e.g., userinterface 122).

In certain implementations, operation 612 may further include anoperation 614 for receiving subjective user state data including dataindicating at least one subjective user state specified by a selectionmade by the user, the selection being a selection of a subjective userstate from at least two indicated alternative contrasting subjectiveuser states as depicted in FIG. 6 a. For instance, the reception module224 (see FIG. 2 c) of the computing device 10 receiving subjective userstate data 60 including data indicating at least one subjective userstate 60 a specified by a selection made by the user 20*, the selectionbeing a selection of a subjective user state from at least two indicatedalternative contrasting subjective user states (e.g., feeling hot,feeling warm, feeling cool, and so forth).

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 616 for acquiring data indicatingoccurrence of at least one subjective mental state of the user asdepicted in FIG. 6 b. For instance, the subjective user state dataacquisition module 104 of the computing device 10 acquiring (e.g., viathe user interface 122 or via the network interface 120) data indicatingoccurrence of at least one subjective mental state of the user 20*.Examples of subjective mental states includes, for example, happiness,sadness, mental fatigue, certain types of pain, alertness, love, envy,disgust or repulsiveness, and so forth.

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 618 for acquiring data indicatingoccurrence of at least one subjective physical state of the user asdepicted in FIG. 6 b. For instance, the subjective user state dataacquisition module 104 of the computing device 10 acquiring (e.g., viathe user interface 122 or via the network interface 120) data indicatingoccurrence of at least one subjective physical state of the user 20*.Examples of subjective physical states include upset stomach, painrelated to different parts of the body, condition of user vision (e.g.,blurry vision), sensitivity of teeth, physical fatigue, and so forth.

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 620 for acquiring data indicatingoccurrence of at least one subjective overall state of the user asdepicted in FIG. 6 b. For instance, the subjective user state dataacquisition module 104 of the computing device 10 acquiring (e.g., viathe user interface 122 or via the network interface 120) data indicatingoccurrence of at least one subjective overall state of the user 20*.Examples of subjective overall states include, “good,” “bad,”“wellness,” and so forth.

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 622 for acquiring a time stampassociated with occurrence of at least one subjective user state asdepicted in FIG. 6 b. For instance, the time stamp acquisition module230 of the computing device 10 acquiring (e.g., via the networkinterface 120, via the user interface 122 as provided by the user 20*,or by automatically generating) a time stamp associated with occurrenceof at least one subjective user state.

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 624 for acquiring an indicationof a time interval associated with occurrence of at least one subjectiveuser state as depicted in FIG. 6 b. For instance, the time intervalacquisition module 231 of the computing device 10 acquiring (e.g., viathe network interface 120, via the user interface 122 as provided by theuser 20*, or by automatically generating) an indication of a timeinterval (e.g., 3 PM to 5 PM) associated with occurrence of at least onesubjective user state (e.g., hunger).

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 626 for acquiring an indicationof a temporal relationship between occurrence of at least one subjectiveuser state and occurrence of at least one objective occurrence asdepicted in FIG. 6 b. For instance, the temporal relationshipacquisition module 232 of the computing device 10 acquiring (e.g., viathe network interface 120, via the user interface 122 as provided by theuser 20*, or by automatically generating) an indication of a temporalrelationship (e.g., before, after, or at least partially concurrently)between occurrence of at least one subjective user state (e.g.,alertness) and occurrence of at least one objective occurrence (e.g.,exercise).

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 628 for acquiring the subjectiveuser state data at a server as depicted in FIG. 6 b. For instance, thesubjective user state data acquisition module 104 of the computingdevice 10 acquiring (e.g., via the network interface 120) the subjectiveuser state data 60 when the computing device 10 is a network server.

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 630 for acquiring the subjectiveuser state data at a handheld device as depicted in FIG. 6 c. Forinstance, the subjective user state data acquisition module 104 of thecomputing device 10 acquiring (e.g., via the user interface 122) thesubjective user state data 60 when the computing device 10 is a localcomputing device such as a handheld device.

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 632 for acquiring the subjectiveuser state data at a peer-to-peer network component device as depictedin FIG. 6 c. For instance, the subjective user state data acquisitionmodule 104 of the computing device 10 acquiring (e.g., via the userinterface 122 or via the network interface 120) the subjective userstate data 60 when the computing device 10 is a peer-to-peer networkcomponent device.

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 634 for acquiring the subjectiveuser state data via a Web 2.0 construct as depicted in FIG. 6 c. Forinstance, the subjective user state data acquisition module 104 of thecomputing device 10 acquiring (e.g., via the user interface 122 or viathe network interface 120) the subjective user state data 60 when thecomputing device 10 is executing a Web 2.0 construct (e.g., Web 2.0application).

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 636 for acquiring data indicatingat least one subjective user state that occurred at least partiallyconcurrently with an incidence of the at least one objective occurrenceas depicted in FIG. 6 c. For instance, the subjective user state dataacquisition module 104 of the computing device 10 acquiring (e.g., viathe user interface 122 or via the network interface 120) data indicatingat least one subjective user state (e.g., happiness) that occurred atleast partially concurrently with an incidence of the at least oneobjective occurrence (e.g., boss going on a vacation).

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 638 for acquiring data indicatingat least one subjective user state that occurred prior to an incidenceof the at least one objective occurrence as depicted in FIG. 6 c. Forinstance, the subjective user state data acquisition module 104 of thecomputing device 10 acquiring (e.g., via the user interface 122 or viathe network interface 120) data indicating at least one subjective userstate (e.g., anxiety) that occurred prior to an incidence of the atleast one objective occurrence (e.g., exam).

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 640 for acquiring data indicatingat least one subjective user state that occurred subsequent to anincidence of the at least one objective occurrence as depicted in FIG. 6c. For instance, the subjective user state data acquisition module 104of the computing device 10 acquiring (e.g., via the user interface 122or via the network interface 120) data indicating at least onesubjective user state (e.g., hangover) that occurred subsequent to anincidence of the at least one objective occurrence (e.g., alcoholconsumption by the user 20*).

In some embodiments, the subjective user state data acquisitionoperation 306 may include an operation 642 for acquiring data indicatingat least one subjective user state that occurred within a predefinedtime period of an incidence of the at least one objective occurrence asdepicted in FIG. 6 c. For instance, the subjective user state dataacquisition module 104 of the computing device 10 acquiring (e.g., viathe user interface 122 or via the network interface 120) data indicatingat least one subjective user state (e.g., sore ankle) that occurredwithin a predefined time period (e.g., one day) of an incidence of theat least one objective occurrence (e.g., user 20* playing basketball).

Referring back to FIG. 3, the correlation operation 308 may include oneor more additional operations in various alternative implementations.For example, in some implementations, the correlation operation 308 mayinclude an operation 702 for correlating the subjective user state datawith the objective occurrence data based, at least in part, on adetermination of at least one sequential pattern associated withoccurrence of the at least one subjective user state and occurrence ofthe at least one objective occurrence as depicted in FIG. 7 a. Forinstance, the correlation module 106 of the computing device 10correlating the subjective user state data 60 with the objectiveoccurrence data 70* based, at least in part, on a determination (e.g.,as determined by the sequential pattern determination module 236) of atleast one sequential pattern associated with occurrence of the at leastone subjective user state and occurrence of the at least one objectiveoccurrence.

In various alternative implementations, operation 702 may include one ormore additional operations. For example, in some implementations,operation 702 may include an operation 704 for correlating thesubjective user state data with the objective occurrence data based, atleast in part, on a determination of whether the at least one subjectiveuser state occurred within a predefined time increment from incidence ofthe at least one objective occurrence as depicted in FIG. 7 a. Forinstance, the correlation module 106 of the computing device 10correlating the subjective user state data 60 with the objectiveoccurrence data 70* based, at least in part, on a determination by the“within predefined time increment determination” module 238 (see FIG. 2d), of whether the at least one subjective user state occurred within apredefined time increment from incidence of the at least one objectiveoccurrence.

In some implementations, operation 702 may include an operation 706 forcorrelating the subjective user state data with the objective occurrencedata based, at least in part, on a determination of whether the at leastone subjective user state occurred before, after, or at least partiallyconcurrently with incidence of the at least one objective occurrence asdepicted in FIG. 7 a. For instance, the correlation module 106 of thecomputing device 10 correlating the subjective user state data 60 withthe objective occurrence data 70* based, at least in part, on adetermination by the temporal relationship determination module 239 ofwhether the at least one subjective user state occurred before, after,or at least partially concurrently with incidence of the at least oneobjective occurrence.

In some implementations, operation 702 may include an operation 708 forcorrelating the subjective user state data with the objective occurrencedata based, at least in part, on referencing of historical data asdepicted in FIG. 7 a. For instance, the correlation module 106 of thecomputing device 10 correlating the subjective user state data 60 withthe objective occurrence data 70* based, at least in part, onreferencing by the historical data referencing module 241 of historicaldata 72 (e.g., population trends such as the superior efficacy ofibuprofen as opposed to acetaminophen in reducing toothaches in thegeneral population, user medical data such as genetic, metabolome, orproteome information, historical sequential patterns particular to theuser 20* or to the overall population such as people having a hangoverafter drinking excessively, and so forth).

In various implementations, operation 708 may include one or moreadditional operations. For example, in some implementations, operation708 may include an operation 710 for correlating the subjective userstate data with the objective occurrence data based, at least in part,on the historical data indicating a link between a subjective user statetype and an objective occurrence type as depicted in FIG. 7 a. Forinstance, the correlation module 106 of the computing device 10correlating the subjective user state data 60 with the objectiveoccurrence data 70* based, at least in part, on the historical datareferencing module 241 referencing the historical data 72 indicative ofa link between a subjective user state type and an objective occurrencetype (e.g., historical data 72 suggests or indicates a link between aperson's mental well-being and exercise).

In some instances, operation 710 may further include an operation 712for correlating the subjective user state data with the objectiveoccurrence data based, at least in part, on a historical sequentialpattern as depicted in FIG. 7 a. For instance, the correlation module106 of the computing device 10 correlating the subjective user statedata 60 with the objective occurrence data 70* based, at least in part,on a historical sequential pattern (e.g., a historical sequentialpattern that indicates that people feel more alert after exercising or ahistorical sequential pattern associated with the user 20*).

For example, a previously determined historical sequential patternassociated with the user 20* may have been determined based onpreviously acquired data indicating occurrence of at least a secondsubjective user state 60 b (see FIG. 1 a) and data indicating occurrenceof at least a second objective occurrence. As will be further describedbelow, the previously determined historical sequential pattern (e.g.,second sequential pattern) may then be compared with the determined onesequential pattern (see operation 702) associated with the at least onesubjective user state and the at least one objective occurrence in orderto correlate the subjective user state data 60 with the objectiveoccurrence data 70*.

In some implementations, operation 708 may include an operation 714 forcorrelating the subjective user state data with the objective occurrencedata based, at least in part, on historical medical data as depicted inFIG. 7 a. For instance, the correlation module 106 of the computingdevice 10 correlating the subjective user state data 60 with theobjective occurrence data 70* based, at least in part, on historicalmedical data (e.g., genetic, metabolome, or proteome information ormedical records of the user 20* or of others related to, for example,diabetes or heart disease).

In some implementations, operation 702 may include an operation 716 forcomparing the at least one sequential pattern to a second sequentialpattern to determine whether the at least one sequential pattern atleast substantially matches with the second sequential pattern asdepicted in FIG. 7 b. For instance, the sequential pattern comparisonmodule 242 of the computing device 10 comparing the at least onesequential pattern to a second sequential pattern to determine whetherthe at least one sequential pattern at least substantially matches withthe second sequential pattern.

In various implementations, operation 716 may further include anoperation 718 for comparing the at least one sequential pattern to asecond sequential pattern related to at least a second subjective userstate associated with the user and a second objective occurrence todetermine whether the at least one sequential pattern at leastsubstantially matches with the second sequential pattern as depicted inFIG. 7 b. For instance, the sequential pattern comparison module 242 ofthe computing device 10 comparing the at least one sequential pattern toa second sequential pattern related to at least a second subjective userstate associated with the user 20* and a second objective occurrence todetermine whether the at least one sequential pattern at leastsubstantially matches with the second sequential pattern. In otherwords, comparing the at least one subjective user state and the at leastone objective occurrence associated with the one sequential pattern tothe at least a second subjective user state and the at least a secondobjective occurrence associated with the second sequential pattern inorder to determine whether they substantially match (or do not match) aswell as to determine whether respective temporal or time relationshipsassociated with each of the one sequential pattern and the secondsequential pattern substantially match.

In some implementations, the correlation operation 308 of FIG. 3 mayinclude an operation 720 for correlating the subjective user state datawith the objective occurrence data at a server as depicted in FIG. 7 b.For instance, the correlation module 106 of the computing device 10correlating the subjective user state data 60 with the objectiveoccurrence data 70* when the computing device 10 is a network server.

In some implementations, the correlation operation 308 may include anoperation 722 for correlating the subjective user state data with theobjective occurrence data at a handheld device as depicted in FIG. 7 b.For instance, the correlation module 106 of the computing device 10correlating the subjective user state data 60 with the objectiveoccurrence data 70* when the computing device 10 is a handheld device(e.g., a cellular telephone, a personal digital assistant, and soforth).

In some implementations, the correlation operation 308 may include anoperation 724 for correlating the subjective user state data with theobjective occurrence data at a peer-to-peer network component device asdepicted in FIG. 7 b. For instance, the correlation module 106 of thecomputing device 10 correlating the subjective user state data 60 withthe objective occurrence data 70* when the computing device 10 is apeer-to-peer network component device.

Referring to FIG. 8 illustrating another operational flow 800 inaccordance with various embodiments. Operational flow 800 includesoperations that mirror the operations included in the operational flow300 of FIG. 3. These operations include an objective occurrence dataacquisition operation 802, a subjective user state data solicitationoperation 804, a subjective user state data acquisition operation 806,and a correlation operation 808 that correspond to and mirror theobjective occurrence data acquisition operation 302, the subjective userstate data solicitation operation 304, the subjective user state dataacquisition operation 306, and the correlation operation 308,respectively, of FIG. 3.

In addition, operational flow 800 includes a presentation operation 810for presenting one or more results of the correlating as depicted inFIG. 8. For example, the presentation module 108 of the computing device10 presenting (e.g., transmitting via a network interface 120 orproviding via the user interface 122) one or more results of thecorrelating operation 808 as performed by the correlation module 106.

In various embodiments, the presentation operation 810 may include oneor more additional operations as depicted in FIG. 9. For example, insome implementations, the presentation operation 810 may include anoperation 902 for providing the one or more results of the correlatingvia a user interface. For instance, the user interface indication module254 (see FIG. 2 e) of the computing device 10 indicating (e.g.,displaying or audioally providing) the one or more results (e.g., in theform of an advisory, a warning, an alert, a prediction, and so forth ofa future or past result) of the correlating operation 808 performed bythe correlation module 106 via a user interface 122 (e.g., a displaymonitor, a touchscreen, or an audio system including one or morespeakers).

In some implementations, the presentation operation 810 may include anoperation 904 for transmitting the one or more results of thecorrelating via a network interface. For instance, the network interfacetransmission module 252 (see FIG. 2 e) of the computing device 10transmitting the one or more results (e.g., in the form of an advisory,a warning, an alert, a prediction, and so forth of a future or pastresult) of the correlating operation 808 performed by the correlationmodule 106 via a network interface 120 (e.g., NIC).

In some implementations, the presentation operation 810 may include anoperation 906 for presenting an indication of a sequential relationshipbetween the at least one subjective user state and the at least oneobjective occurrence. For instance, the sequential relationshippresentation module 256 of the computing device 10 presenting (e.g.,transmitting via the network interface 120 or indicating via userinterface 122) an indication of a sequential relationship between the atleast one subjective user state (e.g., headache) and the at least oneobjective occurrence (e.g., drinking beer).

In some implementations, the presentation operation 810 may include anoperation 908 for presenting a prediction of a future subjective userstate resulting from a future objective occurrence associated with theuser. For instance, the prediction presentation module 258 of thecomputing device 10 a prediction of a future subjective user stateassociated with the user 20* resulting from a future objectiveoccurrence. An example prediction might state that “if the user drinksfive shots of whiskey tonight, the user will have a hangover tomorrow.”

In some implementations, the presentation operation 810 may include anoperation 910 for presenting a prediction of a future subjective userstate resulting from a past objective occurrence associated with theuser. For instance, the prediction presentation module 258 of thecomputing device 10 presenting a prediction of a future subjective userstate associated with the user 20* resulting from a past objectiveoccurrence. An example prediction might state that “the user will have ahangover tomorrow since the user drank five shots of whiskey tonight.”

In some implementations, the presentation operation 810 may include anoperation 912 for presenting a past subjective user state in connectionwith a past objective occurrence associated with the user. For instance,the past presentation module 260 of the computing device 10 presenting apast subjective user state associated with the user 20* in connectionwith a past objective occurrence. An example of such a presentationmight state that “the user got depressed the last time it rained.”

In some implementations, the presentation operation 810 may include anoperation 914 for presenting a recommendation for a future action. Forinstance, the recommendation module 262 of the computing device 10presenting a recommendation for a future action. An examplerecommendation might state that “the user should not drink five shots ofwhiskey.”

Operation 914 may, in some instances, include an additional operation916 for presenting a justification for the recommendation. For instance,the justification module 264 of the computing device 10 presenting ajustification for the recommendation. An example justification mightstate that “the user should not drink five shots of whiskey because thelast time the user drank five shots of whiskey, the user got ahangover.”

Those having skill in the art will recognize that the state of the arthas progressed to the point where there is little distinction leftbetween hardware and software implementations of aspects of systems; theuse of hardware or software is generally (but not always, in that incertain contexts the choice between hardware an d software can becomesignificant) a design choice representing cost vs. efficiency tradeoffs.Those having skill in the art will appreciate that there are variousvehicles by which processes and/or systems and/or other technologiesdescribed herein can be effected (e.g., hardware, software, and/orfirmware), and that the preferred vehicle will vary with the context inwhich the processes and/or systems and/or other technologies aredeployed. For example, if an implementer determines that speed andaccuracy are paramount, the implementer may opt for a mainly hardwareand/or firmware vehicle; alternatively, if flexibility is paramount, theimplementer may opt for a mainly software implementation; or, yet againalternatively, the implementer may opt for some combination of hardware,software, and/or firmware. Hence, there are several possible vehicles bywhich the processes and/or devices and/or other technologies describedherein may be effected, none of which is inherently superior to theother in that any vehicle to be utilized is a choice dependent upon thecontext in which the vehicle will be deployed and the specific concerns(e.g., speed, flexibility, or predictability) of the implementer, any ofwhich may vary. Those skilled in the art will recognize that opticalaspects of implementations will typically employ optically-orientedhardware, software, and or firmware.

The foregoing detailed description has set forth various embodiments ofthe devices and/or processes via the use of block diagrams, flowcharts,and/or examples. Insofar as such block diagrams, flowcharts, and/orexamples contain one or more functions and/or operations, it will beunderstood by those within the art that each function and/or operationwithin such block diagrams, flowcharts, or examples can be implemented,individually and/or collectively, by a wide range of hardware, software,firmware, or virtually any combination thereof. In one embodiment,several portions of the subject matter described herein may beimplemented via Application Specific Integrated Circuits (ASICs), FieldProgrammable Gate Arrays (FPGAs), digital signal processors (DSPs), orother integrated formats. However, those skilled in the art willrecognize that some aspects of the embodiments disclosed herein, inwhole or in part, can be equivalently implemented in integratedcircuits, as one or more computer programs running on one or morecomputers (e.g., as one or more programs running on one or more computersystems), as one or more programs running on one or more processors(e.g., as one or more programs running on one or more microprocessors),as firmware, or as virtually any combination thereof, and that designingthe circuitry and/or writing the code for the software and or firmwarewould be well within the skill of one of skill in the art in light ofthis disclosure. In addition, those skilled in the art will appreciatethat the mechanisms of the subject matter described herein are capableof being distributed as a program product in a variety of forms, andthat an illustrative embodiment of the subject matter described hereinapplies regardless of the particular type of signal bearing medium usedto actually carry out the distribution. Examples of a signal bearingmedium include, but are not limited to, the following: a recordable typemedium such as a floppy disk, a hard disk drive, a Compact Disc (CD), aDigital Video Disk (DVD), a digital tape, a computer memory, etc.; and atransmission type medium such as a digital and/or an analogcommunication medium (e.g., a fiber optic cable, a waveguide, a wiredcommunications link, a wireless communication link, etc.).

In a general sense, those skilled in the art will recognize that thevarious aspects described herein which can be implemented, individuallyand/or collectively, by a wide range of hardware, software, firmware, orany combination thereof can be viewed as being composed of various typesof “electrical circuitry.” Consequently, as used herein “electricalcircuitry” includes, but is not limited to, electrical circuitry havingat least one discrete electrical circuit, electrical circuitry having atleast one integrated circuit, electrical circuitry having at least oneapplication specific integrated circuit, electrical circuitry forming ageneral purpose computing device configured by a computer program (e.g.,a general purpose computer configured by a computer program which atleast partially carries out processes and/or devices described herein,or a microprocessor configured by a computer program which at leastpartially carries out processes and/or devices described herein),electrical circuitry forming a memory device (e.g., forms of randomaccess memory), and/or electrical circuitry forming a communicationsdevice (e.g., a modem, communications switch, or optical-electricalequipment). Those having skill in the art will recognize that thesubject matter described herein may be implemented in an analog ordigital fashion or some combination thereof.

Those having skill in the art will recognize that it is common withinthe art to describe devices and/or processes in the fashion set forthherein, and thereafter use engineering practices to integrate suchdescribed devices and/or processes into data processing systems. Thatis, at least a portion of the devices and/or processes described hereincan be integrated into a data processing system via a reasonable amountof experimentation. Those having skill in the art will recognize that atypical data processing system generally includes one or more of asystem unit housing, a video display device, a memory such as volatileand non-volatile memory, processors such as microprocessors and digitalsignal processors, computational entities such as operating systems,drivers, graphical user interfaces, and applications programs, one ormore interaction devices, such as a touch pad or screen, and/or controlsystems including feedback loops and control motors (e.g., feedback forsensing position and/or velocity; control motors for moving and/oradjusting components and/or quantities). A typical data processingsystem may be implemented utilizing any suitable commercially availablecomponents, such as those typically found in datacomputing/communication and/or network computing/communication systems.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely exemplary, and that in fact many other architectures can beimplemented which achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected”, or“operably coupled”, to each other to achieve the desired functionality,and any two components capable of being so associated can also be viewedas being “operably couplable”, to each other to achieve the desiredfunctionality. Specific examples of operably couplable include but arenot limited to physically mateable and/or physically interactingcomponents and/or wirelessly interactable and/or wirelessly interactingcomponents and/or logically interacting and/or logically interactablecomponents.

While particular aspects of the present subject matter described hereinhave been shown and described, it will be apparent to those skilled inthe art that, based upon the teachings herein, changes and modificationsmay be made without departing from the subject matter described hereinand its broader aspects and, therefore, the appended claims are toencompass within their scope all such changes and modifications as arewithin the true spirit and scope of the subject matter described herein.Furthermore, it is to be understood that the invention is defined by theappended claims.

It will be understood by those within the art that, in general, termsused herein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to inventions containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should typically be interpreted to mean “atleast one” or “one or more”); the same holds true for the use ofdefinite articles used to introduce claim recitations.

In addition, even if a specific number of an introduced claim recitationis explicitly recited, those skilled in the art will recognize that suchrecitation should typically be interpreted to mean at least the recitednumber (e.g., the bare recitation of “two recitations,” without othermodifiers, typically means at least two recitations, or two or morerecitations). Furthermore, in those instances where a conventionanalogous to “at least one of A, B, and C, etc.” is used, in generalsuch a construction is intended in the sense one having skill in the artwould understand the convention (e.g., “ a system having at least one ofA, B, and C” would include but not be limited to systems that have Aalone, B alone, C alone, A and B together, A and C together, B and Ctogether, and/or A, B, and C together, etc.).

In those instances where a convention analogous to “at least one of A,B, or C, etc.” is used, in general such a construction is intended inthe sense one having skill in the art would understand the convention(e.g., “ a system having at least one of A, B, or C” would include butnot be limited to systems that have A alone, B alone, C alone, A and Btogether, A and C together, B and C together, and/or A, B, and Ctogether, etc.). It will be further understood by those within the artthat virtually any disjunctive word and/or phrase presenting two or morealternative terms, whether in the description, claims, or drawings,should be understood to contemplate the possibilities of including oneof the terms, either of the terms, or both terms. For example, thephrase “A or B” will be understood to include the possibilities of “A”or “B” or “A and B.”

1. A system comprising: a processor; an objective occurrence dataacquisition module configured to acquire objective occurrence data, theobjective occurrence data to be acquired including data indicatingoccurrence of at least one objective occurrence; a subjective user statedata solicitation module configured to solicit subjective user statedata including data indicating occurrence of at least one subjectiveuser state associated with a user in response to the acquisition of theobjective occurrence data; a subjective user state data acquisitionmodule configured to acquire the subjective user state data; and acorrelation module configured to correlate the objective occurrence datawith the subjective user state data, wherein said correlation moduleconfigured to correlate the objective occurrence data with thesubjective user state data comprises: a sequential pattern determinationmodule configured to determine at least one sequential patternassociated with occurrence of the at least one subjective user state andoccurrence of the at least one objective occurrence.
 2. The system ofclaim 1, wherein said objective occurrence data acquisition moduleconfigured to acquire objective occurrence data, the objectiveoccurrence data to be acquired including data indicating occurrence ofat least one objective occurrence comprises: an objective occurrencedata reception module configured to receive the objective occurrencedata including the data indicating occurrence of at least one objectiveoccurrence.
 3. The system of claim 1, wherein said subjective user statedata solicitation module configured to solicit subjective user statedata including data indicating occurrence of at least one subjectiveuser state associated with a user in response to the acquisition of theobjective occurrence data comprises: a requesting module configured torequest for the data indicating occurrence of at least one subjectiveuser state associated with a user.
 4. The system of claim 3, whereinsaid requesting module configured to request for the data indicatingoccurrence of at least one subjective user state associated with a usercomprises: a requesting module configured to request to be provided withthe data indicating occurrence of at least one subjective user stateassociated with a user.
 5. The system of claim 3, wherein saidrequesting module configured to request for the data indicatingoccurrence of at least one subjective user state associated with a usercomprises: a requesting module configured to have access to the dataindicating occurrence of at least one subjective user state associatedwith a user.
 6. The system of claim 1, wherein said subjective userstate data solicitation module configured to solicit subjective userstate data including data indicating occurrence of at least onesubjective user state associated with a user in response to theacquisition of the objective occurrence data comprises: a configurationmodule designed to configure to obtain the data indicating occurrence ofat least one subjective user state associated with a user.
 7. The systemof claim 1, wherein said subjective user state data solicitation moduleconfigured to solicit subjective user state data including dataindicating occurrence of at least one subjective user state associatedwith a user in response to the acquisition of the objective occurrencedata comprises: a directing/instructing module designed to obtain thedata indicating occurrence of at least one subjective user stateassociated with a user.
 8. The system of claim 1, wherein saidsubjective user state data solicitation module configured to solicitsubjective user state data including data indicating occurrence of atleast one subjective user state associated with a user in response tothe acquisition of the objective occurrence data comprises: a subjectiveuser state data solicitation module configured to solicit the dataindicating occurrence of at least one subjective user state associatedwith a user from the user.
 9. The system of claim 8, wherein saidsubjective user state data solicitation module configured to solicit thedata indicating occurrence of at least one subjective user stateassociated with a user from the user comprises: a user interfacesolicitation module configured to solicit, via a user interface, thedata indicating occurrence of at least one subjective user stateassociated with a user.
 10. The system of claim 9, wherein said userinterface solicitation module configured to solicit, via a userinterface, the data indicating occurrence of at least one subjectiveuser state associated with a user comprises: an indication moduleconfigured to indicate, via at least a display monitor or a touchscreen,a request for the data indicating occurrence of at least one subjectiveuser state associated with a user.
 11. The system of claim 9, whereinsaid user interface solicitation module configured to solicit, via auser interface, the data indicating occurrence of at least onesubjective user state associated with a user comprises: an indicationmodule configured to indicate, via at least an audio system, a requestfor the data indicating occurrence of at least one subjective user stateassociated with a user.
 12. The system of claim 8, wherein saidsubjective user state data solicitation module configured to solicit thedata indicating occurrence of at least one subjective user stateassociated with a user from the user comprises: a network interfacesolicitation module configured to solicit, via a network interface, thedata indicating occurrence of at least one subjective user stateassociated with a user.
 13. The system of claim 12, wherein said networkinterface solicitation module configured to solicit, via a networkinterface, the data indicating occurrence of at least one subjectiveuser state associated with a user comprises: a transmission moduleconfigured to transmit a request for the data indicating occurrence ofat least one subjective user state associated with a user.
 14. Thesystem of claim 8, wherein said subjective user state data solicitationmodule configured to solicit the data indicating occurrence of at leastone subjective user state associated with a user from the usercomprises: a requesting module configured to request for a confirmationof occurrence of a subjective user state.
 15. The system of claim 8,wherein said subjective user state data solicitation module configuredto solicit the data indicating occurrence of at least one subjectiveuser state associated with a user from the user comprises: a requestingmodule configured to request for an indication of occurrence of at leastone subjective user state with respect to occurrence of the at least oneobjective occurrence.
 16. The system of claim 8, wherein said subjectiveuser state data solicitation module configured to solicit the dataindicating occurrence of at least one subjective user state associatedwith a user from the user comprises: a requesting module configured torequest for an indication of a time or temporal element associated withoccurrence of the at least one subjective user state.
 17. The system ofclaim 16, wherein said requesting module configured to request for anindication of a time or temporal element associated with occurrence ofthe at least one subjective user state comprises: a requesting moduleconfigured to request for an indication of a point in time associatedwith the occurrence of the at least one subjective user state.
 18. Thesystem of claim 16, wherein said requesting module configured to requestfor an indication of a time or temporal element associated withoccurrence of the at least one subjective user state comprises: arequesting module configured to request for an indication of a timeinterval associated with the occurrence of the at least one subjectiveuser state.
 19. The system of claim 16, wherein said requesting moduleconfigured to request for an indication of a time or temporal elementassociated with occurrence of the at least one subjective user statecomprises: a requesting module configured to request for an indicationof a temporal relationship between occurrence of the at least onesubjective user state and occurrence of at least one objectiveoccurrence.
 20. The system of claim 1, wherein said subjective userstate data solicitation module configured to solicit subjective userstate data including data indicating occurrence of at least onesubjective user state associated with a user in response to theacquisition of the objective occurrence data comprises: a subjectiveuser state data solicitation module configured to solicit dataindicating occurrence of at least one subjective mental state associatedwith the user.
 21. The system of claim 1, wherein said subjective userstate data solicitation module configured to solicit subjective userstate data including data indicating occurrence of at least onesubjective user state associated with a user in response to theacquisition of the objective occurrence data comprises: a subjectiveuser state data solicitation module configured to solicit dataindicating occurrence of at least one subjective physical stateassociated with the user.
 22. The system of claim 1, wherein saidsubjective user state data solicitation module configured to solicitsubjective user state data including data indicating occurrence of atleast one subjective user state associated with a user in response tothe acquisition of the objective occurrence data comprises: a subjectiveuser state data solicitation module configured to solicit dataindicating occurrence of at least one subjective overall stateassociated with the user.
 23. The system of claim 1, wherein saidsubjective user state data solicitation module configured to solicitsubjective user state data including data indicating occurrence of atleast one subjective user state associated with a user in response tothe acquisition of the objective occurrence data comprises: a subjectiveuser state data solicitation module configured to solicit dataindicating occurrence of at least one subjective user state during aspecified point in time.
 24. The system of claim 1, wherein saidsubjective user state data solicitation module configured to solicitsubjective user state data including data indicating occurrence of atleast one subjective user state associated with a user in response tothe acquisition of the objective occurrence data comprises: a subjectiveuser state data solicitation module configured to solicit dataindicating occurrence of at least one subjective user state during aspecified time interval.
 25. The system of claim 1, wherein saidsubjective user state data solicitation module configured to solicitsubjective user state data including data indicating occurrence of atleast one subjective user state associated with a user in response tothe acquisition of the objective occurrence data comprises: a subjectiveuser state data solicitation module configured to solicit the dataindicating occurrence of at least one subjective user state in responseto the acquisition of the objective occurrence data and in response tohistorical data.
 26. The system of claim 25, wherein said subjectiveuser state data solicitation module configured to solicit the dataindicating occurrence of at least one subjective user state in responseto the acquisition of the objective occurrence data and in response tohistorical data comprises: a subjective user state data solicitationmodule configured to solicit the data indicating occurrence of at leastone subjective user state based, at least in part, on one or morehistorical sequential patterns.
 27. The system of claim 25, wherein saidsubjective user state data solicitation module configured to solicit thedata indicating occurrence of at least one subjective user state inresponse to the acquisition of the objective occurrence data and inresponse to historical data comprises: a subjective user state datasolicitation module configured to solicit the data indicating occurrenceof at least one subjective user state based, at least in part, onmedical data.
 28. The system of claim 25, wherein said subjective userstate data solicitation module configured to solicit the data indicatingoccurrence of at least one subjective user state in response to theacquisition of the objective occurrence data and in response tohistorical data comprises: a subjective user state data solicitationmodule configured to solicit the data indicating occurrence of at leastone subjective user state based, at least in part, on historical datathat indicates a link between an objective occurrence type and asubjective user state type.
 29. The system of claim 25, wherein saidsubjective user state data solicitation module configured to solicit thedata indicating occurrence of at least one subjective user state inresponse to the acquisition of the objective occurrence data and inresponse to historical data comprises: a subjective user state datasolicitation module configured to solicit the data indicating occurrenceof at least one subjective user state, the solicitation prompted, atleast in part, by the historical data.
 30. The system of claim 25,wherein said subjective user state data solicitation module configuredto solicit the data indicating occurrence of at least one subjectiveuser state in response to the acquisition of the objective occurrencedata and in response to historical data comprises: a subjective userstate data solicitation module configured to solicit data indicatingoccurrence of a particular or a particular type of subjective user statebased on the historical data.
 31. The system of claim 1, wherein saidsubjective user state data solicitation module configured to solicitsubjective user state data including data indicating occurrence of atleast one subjective user state associated with a user in response tothe acquisition of the objective occurrence data comprises: a subjectiveuser state data solicitation module configured to solicit data thatindicates one or more attributes associated with the at least onesubjective state.
 32. The system of claim 1, wherein said subjectiveuser state data acquisition module configured to acquire the subjectiveuser state data comprises: a subjective user state data user interfacereception module configured to receive, via a user interface, thesubjective user state data.
 33. The system of claim 1, wherein saidsubjective user state data acquisition module configured to acquire thesubjective user state data comprises: a subjective user state datanetwork interface reception module configured to receive, via a networkinterface, the subjective user state data.
 34. The system of claim 33,wherein said subjective user state data network interface receptionmodule configured to receive, via a network interface, the subjectiveuser state data comprises: a subjective user state data networkinterface reception module configured to receive an electronic messagegenerated by the user, the electronic message including data indicatingthe at least one subjective user state.
 35. The system of claim 33,wherein said subjective user state data network interface receptionmodule configured to receive, via a network interface, the subjectiveuser state data comprises: a subjective user state data networkinterface reception module configured to receive a blog entry generatedby the user, the blog entry including data indicating the at least onesubjective user state.
 36. The system of claim 33, wherein saidsubjective user state data network interface reception module configuredto receive, via a network interface, the subjective user state datacomprises: a subjective user state data network interface receptionmodule configured to receive a status report generated by the user, thestatus report including data indicating the at least one subjective userstate.
 37. The system of claim 1, wherein said sequential patterndetermination module configured to determine at least one sequentialpattern associated with occurrence of the at least one subjective userstate and occurrence of the at least one objective occurrence comprises:a historical data reference module configured to reference historicaldata to correlate the subjective user state data with the objectiveoccurrence data.
 38. The system of claim 1, wherein said sequentialpattern determination module configured to determine at least onesequential pattern associated with occurrence of the at least onesubjective user state and occurrence of the at least one objectiveoccurrence comprises: a sequential pattern comparison module configuredto compare the at least one sequential pattern to a second sequentialpattern to determine whether the at least one sequential pattern atleast substantially matches with the second sequential pattern.
 39. Asystem comprising: a processor; an objective occurrence data acquisitionmodule configured to acquire objective occurrence data, the objectiveoccurrence data to be acquired including data indicating occurrence ofat least one objective occurrence; a subjective user state datasolicitation module configured to solicit subjective user state dataincluding data indicating occurrence of at least one subjective userstate associated with a user in response to the acquisition of theobjective occurrence data, wherein said subjective user state datasolicitation module configured to solicit subjective user state dataincluding data indicating occurrence of at least one subjective userstate associated with a user in response to the acquisition of theobjective occurrence data comprises: a subjective user state datasolicitation module configured to solicit the data indicating occurrenceof at least one subjective user state associated with a user from theuser, wherein said subjective user state data solicitation moduleconfigured to solicit the data indicating occurrence of at least onesubjective user state associated with a user from the user comprises: arequesting module configured to request for a selection of a subjectiveuser state from a plurality of indicated alternative subjective userstates; a subjective user state data acquisition module configured toacquire the subjective user state data; and a correlation moduleconfigured to correlate the objective occurrence data with thesubjective user state data.
 40. The system of claim 39, wherein saidrequesting module configured to request for a selection of a subjectiveuser state from a plurality of indicated alternative subjective userstates comprises: a requesting module configured to request for aselection of a subjective user state from a plurality of indicatedalternative contrasting subjective user states.
 41. An article ofmanufacture, comprising: a non-transitory storage medium bearing: one ormore instructions for acquiring objective occurrence data, the objectiveoccurrence data to be acquired including data indicating occurrence ofat least one objective occurrence; one or more instructions forsoliciting subjective user state data including data indicatingoccurrence of at least one subjective user state associated with a userin response to the acquisition of the objective occurrence data; one ormore instructions for acquiring the subjective user state data; and oneor more instructions for correlating the objective occurrence data withthe subjective user state data, wherein said one or more instructionsfor correlating the objective occurrence data with the subjective userstate data comprises: one or more instructions for determining at leastone sequential pattern associated with occurrence of the at least onesubjective user state and occurrence of the at least one objectiveoccurrence.